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
Sammendrag
Det er ikke registrert sammendrag
Sammendrag
The effectiveness of generating virtual transects on unmanned aerial vehicle-derived orthomosaics was evaluated in estimating the extent of soil disturbance by severity class. Combinations of 4 transect lengths (5–50 m) and five sampling intensities (1–20 transects per ha) were used in assessing traffic intensity and the severity of soil disturbance on six post-harvest, cut-to-length (CTL) clearfell sites. In total, 15% of the 33 ha studied showed some trace of vehicle traffic. Of this, 63% of was categorized as light (no visible surface disturbance). Traffic intensity varied from 787 to 1256 m ha−1, with a weighted mean of 956 m ha−1, approximately twice the geometrical minimum achievable with CTL technology under perfect conditions. An overall weighted mean of 4.7% of the total site area was compromised by severe rutting. A high sampling intensity, increasing with decreasing incidence of soil disturbance, is required if mean estimation error is to be kept below 20%. The paper presents a methodology that can be generally applied in forest management or in similar land-use evaluations.
Forfattere
Kris Verheyen Martin Bažány Ewa Chećko Markéta Chudomelová Déborah Closset-Kopp Patryk Czortek Guillaume Decocq Pieter De Frenne Luc De Keersmaeker Cecilia Enriquez Garcia Martina Fabšičová John-Arvid Grytnes Lucia Hederová Radim Hédl Thilo Heinken Fride Høistad Schei Soma Horváth Bogdan Jaroszewicz Edyta Jermakowicz Terezá Klinerova Jens Kolk Martin Kopecký Iwona Kuras Jonathan Lenoir Martin Macek František Máliš Tone Constance Martinessen Tobias Naaf László Papp Ágnes Papp-Szákaly Paweł Pech Petr Petřík Jindřich Prach Kamila Reczýnska Magne Sætersdal Fabien Spicher Tibor Standovár Krzysztof Świerkosz Ewa Szczęśniak Zoltán Tóth Karol Ujházy Mariana Ujházyová Pieter Vangansbeke Ondřej Vild Dan Wołkowycki Monika Wulf Lander BaetenSammendrag
Aim: Revisits of non-permanent, relocatable plots first surveyed several decades ago offer a direct way to observe vegetation change and form a unique and increasingly used source of information for global change research. Despite the important insights that can be obtained from resurveying these quasi-permanent vegetation plots, their use is prone to both observer and relocation errors. Studying the combined effects of both error types is important since they will play out together in practice and it is yet unknown to what extent observed vegetation changes are influenced by these errors. Methods: We designed a study that mimicked all steps in a resurvey study and that allowed determination of the magnitude of observer errors only vs the joint observer and relocation errors. Communities of vascular plants growing in the understorey of temperate forests were selected as study system. Ten regions in Europe were covered to explore generality across contexts and 50 observers were involved, which deliberately differed in their experience in making vegetation records. Results: The mean geographic distance between plots in the observer+relocation error data set was 24 m. The mean relative difference in species richness in the observer error and the observer+relocation data set was 15% and 21%, respectively. The mean “pseudo-turnover” between the five records at a quasi-permanent plot location was on average 0.21 and 0.35 for the observer error and observer+relocation error data sets, respectively. More detailed analyses of the compositional variation showed that the nestedness and turnover components were of equal importance in the observer data set, whereas turnover was much more important than nestedness in the observer+relocation data set. Interestingly, the differences between the observer and the observer+relocation data sets largely disappeared when looking at temporal change: both the changes in species richness and species composition over time were very similar in these data sets. Conclusions: Our results demonstrate that observer and relocation errors are nonnegligible when resurveying quasi-permanent plots. A careful interpretation of the results of resurvey studies is warranted, especially when changes are assessed based on a low number of plots. We conclude by listing measures that should be taken to maximally increase the precision and the strength of the inferences drawn from vegetation resurveys.
Forfattere
Anders Arvesen Francesco Cherubini Gonzalo del Alamo Serrano Rasmus Astrup Michael Becidan Helmer Belbo Franziska Goile Tuva Grytli Geoffrey Guest Carine Lausselet Per Kr. Rørstad Line Rydså Morten Seljeskog Øyvind Skreiberg Veena Sajith Vezhapparambu Anders Hammer StrømmanSammendrag
Climate impacts of forest bioenergy result from a multitude of warming and cooling effects and vary by location and technology. While past bioenergy studies have analysed a limited number of climatealtering pollutants and activities, no studies have jointly addressed supply chain greenhouse gas emissions, biogenic CO2 fluxes, aerosols and albedo changes at high spatial and process detail. Here, we present a national-level climate impact analysis of stationary bioenergy systems in Norway based on wood-burning stoves and wood biomass-based district heating. We find that cooling aerosols and albedo offset 60–70% of total warming, leaving a net warming of 340 or 69 kg CO2e MWh−1 for stoves or district heating, respectively. Large variations are observed over locations for albedo, and over technology alternatives for aerosols. By demonstrating both notable magnitudes and complexities of different climate warming and cooling effects of forest bioenergy in Norway, our study emphasizes the need to consider multiple forcing agents in climate impact analysis of forest bioenergy.
Sammendrag
It is recognised that flame retardant chemicals degrade and leach out of flame-protected wood claddings when exposed to natural weathering. However, the ability to survey the current state of a flame retardant treatment applied to a wood cladding, an arbitrary length of time after the initial application, is limited today. In this study, hyperspectral imaging in the near infrared to short-wavelength infrared region is used to quantify the amount of flame retardant present on wooden surfaces. Several sets of samples were treated with various concentrations of a flame retardant chemical and scanned with a push broom hyperspectral camera. An inductively coupled plasma (ICP) spectroscopy analysis of the outermost layer of the treated samples was then carried out in order to determine each sample’s phosphorus content, the active ingredient in the flame retardant. Spectra from the hyperspectral images were pre-processed with extended multiplicative scatter correction, and the phosphorus content was modelled using a partial least squares (PLS) regression model. The PLS regression yielded robust predictions of surface phosphorus content with a coefficient of determination, R2, between 0.8 and 0.9 on validation data regardless of whether the flame retardant chemical had been applied to the surface of the wood or pressure-impregnated into it. The result from the study indicates that spectral imaging around the 2400–2531nm wavelength region is favourable for quantifying the amount of phosphorus-based flame retardant contained in the outermost layer of non-coated wooden claddings. The results also reveal that the uptake of phosphorus-based flame retardant does not occur uniformly throughout the wood surface, but is to a larger extent concentrated in the earlywood regions than in the latewood.
Sammendrag
The aim of this research is to determine if the polyesterification of sorbitol and citric acid in wood has a future potential as a wood modification process. Pine wood was impregnated with an aqueous solution containing citric acid and sorbitol and was thereafter cured at 103 or 140°C for 18 hours. The dimensional stability and leaching resistance were studied for both modification temperatures. The leachates from the modified wood samples were analysed by HPLC and the susceptibility to decay and staining fungi were studied. Impregnated samples cured at 140°C showed a permanent (leach-resistant) increased dimensional change, but samples treated at 103°C were not stable to leaching. Treated samples cured at 103 and 140°C showed significant resistance to white-rot (Trametes versicolor) and brown-rot decay (Postia placenta) after a leaching procedure. Furthermore, samples cured at 103 and 140°C (leached and unleached) were significantly less susceptible to blue-stain fungi than the untreated controls.
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Lise Grøva Boris Fuchs Emma Brunberg Unni Støbet Lande Kristin Sørheim Svein-Olaf Hvasshovd Solveig Marie StubsjøenSammendrag
SENSOR TECHNOLOGY TO DETECT TICK-BORNE FEVER IN SHEEP ON RANGE PASTURE? Lise GRØVA 1), Boris Fuchs 2), Emma BRUNBERG 3), Unni Støbet LANDE 2), Kristin SØRHEIM 2), Svein Olav Hvasshovd 4), Solveig Marie Stubsjøen 5) 1) NIBIO, Norwegian Institute of Bioeconomy Research, Gunnars veg 6, 6630 Tingvoll, Norway; lise.grova@nibio.no 2) Inland Norway University of Applied Sciences, Campus Evenstad, Elverum, Norway 3) NORSØK, Norwegian Centre for Organic Agriculture, Gunnars veg 6, 6630 Tingvoll, Norway; emma.brunberg@djurskyddet.se 4) NTNU, Norwegian University of Science and Technology, Trondheim, Norway 5) VETINST, Norwegian Veterinary Institute, Oslo, Norway More than two million sheep graze on unimproved, rough grazing land during the summer months each year in Norway. Free ranging sheep are perceived to experience high level of animal welfare through their opportunity to perform natural behaviour, but these benefits are compromised when sheep experience predator attacks, disease and accidents. Ensuring animal health and welfare in farming systems gets increased attention, and new policies and legislations are implemented. About 125 000 sheep (6-7%) are lost on such pastures every year. Tick-borne fever (TBF) is a disease considered to be a major challenge in sheep farming during the grazing season along the coast of south-western Norway. Clinical signs of TBF is ofte observed within 14 days of infection, starting with an abrupt rise in rectal temperature (often above 41o C). Being able to monitor farm animals on range pastures is increasingly important and implementing available technology for this purpose should be exploited. Implementation of sensor technology in rangeland sheep farming can monitor physiological parameters, such as body temperature (T). Integrating such sensors in a GPS tracking system may contribute to detect, locate and treat sick animals, as well as improve our knowledge of animal health in time and space in rangeland farming systems. The objective of the work presented here is to evaluate if a temperature sensor can be used for early detection of Tick-borne fever (TBF). In 2016, temperature sensors (Star Oddi, Iceland) were implanted in the abdomen of 20 lambs in a one sheep flock in a TBF risk area and in 20 lambs from one flock in a non-TBF risk area in Norway. The sensors were programmed to log temperature every 10 minutes, and were implanted in lambs in early June and collected in early September to retrieve data. Temperature data were obtained from 13 temperature loggers from lambs in the TBF risk are and 14 loggers in the non-TBF risk area. The telemetry system (Telespor, Norway) was used on all lambs, and provided accelerometer information and real-time positioning data that was used for continuous surveillance on range pasture. All animals were monitored twice a day for approximately one month period after turned out on tick infested pastures. Number and magnitude of fever was calculated for each lamb. Preliminary results from this study will be presented at the conference. Keywords: sheep, sensor technology, temperature, tick-borne fever, rangeland
Forfattere
Lise Grøva Boris Fuchs Emma Brunberg Unni Støbet Lande Kristin Sørheim Svein-Olaf Hvasshovd Solveig Marie StubsjøenSammendrag
Can sensor technology and real-time communication detect tick-born fever in sheep on range pasture? Introduction: More than two million sheep graze on unimproved, rough grazing land during the summer months each year in Norway. Free ranging sheep are perceived to experience high level of animal welfare through their opportunity to perform natural behaviour, but these benefits are compromised when sheep experience predator attacks, disease and accidents. Ensuring animal health and welfare in farming systems gets increased attention, and new policies and legislations are implemented. About 125 000 sheep (6-7%) are lost on such pastures every year. Tick-borne fever (TBF) is a disease considered to be a major challenge in sheep farming during the grazing season along the coast of south-western Norway. Clinical signs of TBF is often observed within 14 days of infection, starting with an abrupt rise in rectal temperature (often above 41o C). Being able to monitor farm animals on range pastures is increasingly important and implementing available technology for this purpose should be exploited. Implementation of sensor technology in rangeland sheep farming can monitor physiological parameters, such as body temperature (T) and heart rate (HR). Integrating sensors that communicate in a GPS tracking system may contribute to detect, locate and treat sick animals, as well as improve our knowledge of animal health in time and space in rangeland farming systems. Sensors for sheep that communicate with a GPS system is not commercially available today. The objective of the work presented here is to evaluate if temperature sensor information can be used for early detection of tick-borne fever (TBF). Materials and methods: In 2016, temperature sensors (T) (CentiT Star Oddi, Iceland) were implanted in the abdomen of 20 lambs in a sheep flock in a TBF risk area (coastal herd) and in 20 lambs from one flock in a non-TBF risk area (inland heard) in Norway. The sensors were programmed to log temperature every 10 minutes, and were implanted in lambs in early June and collected in early September to retrieve data. The telemetry system (Telespor, Norway) was used on all lambs, and provided real-time positioning data that was used for continuous surveillance on range pasture. All lambs were monitored twice a day for clinical assessment for a one month period after they were turned out on pasture and weight was recorded at birth, spring and autumn. Remaining lambs in the coastal and inland flock were used as control for effect of sensor implantation on weight gain. Number of fever incidences and magnitude of fever was calculated by estimating area under curve (auc) for each temperature incidence for each lamb. Results: In total 32 (80 %) of 40 implanted T sensors could be retrieved. From the coastal herd 17 of 20 T sensors could be retrieved and from the inland herd 15 of 20 Tb sensors could be retrieved. All 17 retrieved T sensors from the coastal herd and all 15 sensors of the inland herd worked as programmed. All lost sensor were not detected at retrieval as no lambs were missing. Temperature of all lambs in both herds ranged from 36.9 °C to 41.8 °C with a mean of 39.6°C (SD 0.35). Sensor implantation did not affect weight gain. There was a significant difference in fever incidences and magnitude of fever in lambs in the TBF risk area (coastal heard) compared to the lambs in the non-TBF risk area (inland herd). Conclusion: The study shows that real-time temperature information in lambs has potential as a disease alarm.
Sammendrag
Unmanned aerial vehicles (UAVs) are increasingly used as tools to perform a detailed assessment of post-harvest sites. One of the potential use of UAV photogrammetric data is to obtain tree-stump information that can then be used to support more precise decisions. This study developed and tested a methodology to automatically detect, segment, classify, and measure tree-stumps. Among the potential applications for single stump data, this study assessed the possibility (1) to detect and map root- and butt-rot on the stumps using a machine learning approach, and (2) directly measure or model tree stump diameter from the UAV data. The results revealed that the tree-stumps were detected with an overall accuracy of 68–80%, and once the stump was detected, the presence of root- and butt-rot was detected with an accuracy of 82.1%. Furthermore, the root mean square error of the UAV-derived measurements or model predictions for the stump diameter was 7.5 cm and 6.4 cm, respectively, and with the former systematically under predicting the diameter by 3.3 cm. The results of this study are promising and can lead to the development of more cost-effective and comprehensive UAV post-harvest surveys.