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
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.
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The ericaceous shrub bilberry (Vaccinium myrtillus L.) is a keystone species of the Eurasian boreal forest. The most optimal light condition for this plant is partial shading. Shade from the forest canopy depends on the stand density, a forest attribute that can be manipulated by forest managers. Most previous studies of the relationship between bilberry abundance and forest density have not explored the potentially modifying impacts of factors like stand age, tree species composition, and the solar irradiation at the site, as determined by location and topography. Using data from the Norwegian National Forest Inventory, we developed a generalized linear model applicable to estimate local bilberry cover across a wide range of environmental conditions in Norway. The explanatory terms in the final model were stand density (basal area per ha), solar irradiation, stand age, percentages of deciduous, pine, and spruce trees, summer (June-August) mean temperature and precipitation sum, mean temperature in January, site index, and soil category, in addition to the two-way interactions between stand density and the following: solar irradiation, stand age, percentage of deciduous trees, and percentage of Norway spruce (Picea abies). The final model explained ca. 21% of the total variation in bilberry cover. We conclude that a stand density of c. 30 m2 ha−1 in general will create favourable conditions for bilberry. If the forest is younger than 80 years old, or dominated by Norway spruce or deciduous trees, the optimal stand density is reduced to around 20 m2 ha−1. In a forest dominated by Scots pine (Pinus sylvestris), basal areas up to 40 m2 ha−1 would be beneficial to bilberry abundance. Our results demonstrate the importance of considering interactions between stand density and other stand and site characteristics.
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The long-term success of sites selected for species conservation depends on the persistence of target species. Red List species or threatened species lists are frequently defined as target species, but when Red Lists are updated, their species composition may change. Here we investigate the effects of Red List updates on the long-term robustness of fine-scale site selection. We used records of red-listed species (vascular plants, bryophytes, macrolichens, and polypore fungi) recorded in 1997–1998 in 1058 sample plots (50 × 50 m) from six forest landscapes in Norway, and four consecutive issues of the Norwegian Red List for species (1998, 2006, 2010, 2015). Sites were selected based on the first issue (1998) using both a scoring (“hotspot”) approach and a complementarity approach, and the ability of selected sites to include red-listed species of later issues was measured. In four boreal forests the mean proportion of red-listed species included in selected sites were reduced by18% during the study period, whereas no such effect was found in two hemiboreal forests, where increased clustering of red-listed species in sites compensated for target species changes. Changing target species adds to earlier documented challenges caused by population dynamics, and we suggest that alternatives to using occurrences of target species in site selection should be considered, and particularly at finer spatial scales.
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