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.
2023
Forfattere
Håvard EikemoSammendrag
Potetkreft er en fryktet sykdom i potetdyrkingen, siden den kan føre til totalt avlingstap hvis den ikke bekjempes. Den har ikke vært påvist i Norge siden 1994, men økende forekomster i Sverige og Danmark de siste årene har gjort sjukdommen mer aktuell. Utbruddene i Sverige og Danmark har også vært forårsaket av raser som kan angripe mange av de vanligste potetsortene i Norge. Formålet med dette OK-programmet er å sjekke tilstedeværelse av potetkreft i Norge, samt teste metodikken rundt visuell påvisning og molekylær testing for potetkreft. Selv om man regner potetkreft som ikke forekommende i Norge er det viktig å gjennomføre denne typen undersøkelser for å få dokumentert statusen. Totalt ble 345 prøver vurdert i 2022, og alle var negative ved visuell bedømmelse. Det ble heller ikke funnet noe mistenkelig som førte til at prøvene burde kontrolleres ved PCR. Av de 345 prøvene ble 50 prøver tilfeldig valgt ut for testing ved hjelp av PCR, og også disse var negative. Resultatene fra 2022 viser at status for potetkreft i Norge i henhold til ISPM 8 er å anse som «Absent: pest no longer present».
Sammendrag
Norsk institutt for bioøkonomi utførte somrane 2021 og 2022 vegetasjonskartlegging i Vestre Slidre kommune. Samla areal er 210 km². Kartlegginga er gjort etter instruks for kartlegging i målestokk 1:20 000 - 50 000 (VK25). Det er laga vegetasjonskart og to avleia temakart for beite for sau og storfe. Denne rapporten beskriv metode for kartlegging, registrerte vegetasjonstypar og deira fordeling i området. Det er gjeve ein omtale av beiteverdi og beitekapasitet, samt nokre råd kring skjøtsel av kulturlandskap og beite.
Forfattere
Chathura Palliyaguru Vindhya Basnayake Randika K. Makumbura Miyuru Gunathilake Nitin Muttil Eranga M. Wimalasiri Upaka RathnayakeSammendrag
Soil degradation is a serious environmental issue in many regions of the world, and Sri Lanka is not an exception. Maha Oya River Basin (MORB) is one of the major river basins in tropical Sri Lanka, which suffers from regular soil erosion and degradation. The current study was designed to estimate the soil erosion associated with land use changes of the MORB. The Revised Universal Soil Loss Equation (RUSLE) was used in calculating the annual soil erosion rates, while the Geographic Information System (GIS) was used in mapping the spatial variations of the soil erosion hazard over a 30-year period. Thereafter, soil erosion hotspots in the MORB were also identified. The results of this study revealed that the mean average soil loss from the MORB has substantially increased from 2.81 t ha−1 yr−1 in 1989 to 3.21 t ha−1 yr−1 in 2021, which is an increment of about 14.23%. An extremely critical soil erosion-prone locations (average annual soil loss > 60 t ha−1 yr−1) map of the MORB was developed for the year 2021. The severity classes revealed that approximately 4.61% and 6.11% of the study area were in high to extremely high erosion hazard classes in 1989 and 2021, respectively. Based on the results, it was found that the extreme soil erosion occurs when forests and vegetation land are converted into agricultural and bare land/farmland. The spatial analysis further reveals that erosion-prone soil types, steep slope areas, and reduced forest/vegetation cover in hilly mountain areas contributed to the high soil erosion risk (16.56 to 91.01 t ha−1 yr−1) of the MORB. These high soil erosional areas should be prioritized according to the severity classes, and appropriate land use/land cover (LU/LC) management and water conservation practices should be implemented as recommended by this study to restore degraded lands.
Sammendrag
Mulighetene for et mest mulig plantebasert kosthold basert på norske arealressurser er beskrevet gitt ulike alternativer for framtidig avlingsnivå og arealbruk i planteproduksjonen anslått ut fra agroklimatiske forhold. Rommet for kjøttproduksjon på arealer som ikke blir brukt til matvekster og økt konsum av fisk er også vurdert. Med dette som bakgrunn er det beregnet en potensiell sjølforsyningsgrad, dvs. hvor stor del av befolkningens næringsbehov som vil kunne dekkes av matvarer produsert med basis i norske ressurser. Det er også vurdert hvordan i dag ubrukte beiteressurser i utmark og på innmarksbeiter kan utnyttes. Med det som ble vurdert som maksimalavlinger av korn, olje- og belgvekster hvert år, kunne et 100 % plantebasert kosthold produsert på de høgeste anslagene for matvekstareal gi nok energi, protein og fett til Norges befolkning i 2050. Det ble da lagt til grunn at stordelen av det anbefalte inntaket av grønnsaker og frukt og bær ble dekt av lagringsgrønnsaker som gulrot, kålrot, hodekål og kepaløk, og av epler og konservert jordbær og bringebær. Videre, så forutsatte det at både bygg, havre, hvete, åkerbønner og oljevekster måtte kunne prosesseres til attraktive matvarer, og at proteinet og fettet i dem var av ernæringsmessig høg nok kvalitet. Svikt i forutsetningene om store avlinger og høgt matvekstareal ville sette ned sjølforsyningsgraden betydelig. Moderate og låge avlinger kunne ikke bidra til full sjølforsyning sjøl om et fiskeforbruk sju ganger større enn dagens kostholdsråd kom til erstatning for noen av planteproduktene. Dersom et plantebasert kostholdsalternativ ble realisert, ville det meste av dyrkajorda utenfor flatbygdene i Rogaland, på Østlandet og i Trøndelag ha gått ut av matproduksjon. I kostholdsalternativene med innslag av husdyrprodukter ble det brukt noe areal utenfor flatbygdene til å dyrke grovfôr til melkeproduksjon og tilhørende kjøttproduksjon, og litt av kornarealet ble brukt til å dyrke kraftfôr til denne produksjonen. Omtrent 14 % av energibehovet ble da dekt av animalske produkter. Så lenge protein- og oljevekster og stordelen av kornet ble spist direkte av mennesker og en forutsatte det høgeste avlingsalternativet, kunne dette kostholdet baseres på norske arealressurser aleine. En variant der svinekjøtt gikk inn kostholdet i tillegg til melk og storfekjøtt, og der animalske produkter dekte omtrent 30 % av energibehovet, var ikke mulig å realisere på norske arealressurser. Sjøl med det høgeste avlingsalternativet ble det for lite kornareal.
Forfattere
Andres Perea Lara Macon Sajidur Rahman Huiying Chen Andrew Cox Shelemia Nyamuryekung'e Sara Campa Madrid Huiping Cao Andres F. Cibils Richard Estell Glenn Duff Santiago A. UtsumiSammendrag
Monitoring cattle on rangelands is a daunting task that can be improved by using wearable sensors that are capable of transmitting motion and position data in real time and at low cost. This study tested the performance of machine learning (ML) classifiers to discriminate among foraging activities of cows based on triaxial accelerometer data collected in real-time by LoRa WAN networks. Trials were conducted at the New Mexico State University Chihuahuan Desert Rangeland Research Center and the USDA Jornada Experimental Range in Doña Ana County, NM. A total of 24 Brangus, Brahman, Raramuri Criollo and Angus x Hereford mature cows fitted with LoRa WAN tracking collars housing GPS and triaxial accelerometers were monitored across four periods during the 2022 summer and fall seasons on desert rangeland pastures. Trackers integrated and transmitted activity count (Ac) data from accelerometers at one-minute intervals. Video recording of focal cows (n = 24) was undertaken during daylight hours (0630 to 2000 h) from a distance of ~30 m to minimize interference with natural behaviors. A total of 168 hours of video were recorded and inspected by an experienced observer to label video files according to a classification tree of four main activities: grazing (GR), walking (WA), resting (RE) and ruminating (RU), and two states: active (AC) or static (ST). Individualized activities and states were considered when cows performed the same predefined activity or state for more than 30 secs. Retrieved sensor data from collar trackers were labeled by state and activity according to labels collected from video records. This classification resulted in a dataset containing 9,222 events, including 3,928 for GR, 2,286 for WA, 2,032 for RE, and 976 for RU, as well as 6,214 labels for AC and 3,008 labels for ST. Deep learning through Multilayer Perceptron Classifiers (MLPC) were coded and implemented using a split configuration of 70% of the data for training and 30% for testing, respectively. In preliminary runs, models had reduced ability to properly discriminate among RE (F1 = 0.42) and RU (F1 = 0.43) Thus, RE and RU were merged on subsequent tests, resulting in 3,928 labels for GR, 2,286 labels for WA, and 3,008 labels for merged RE. Deep learning models successfully classified between AC vs. ST behavior with an overall F1 performance score of 0.96. Further use of the same deep learning models successfully classified among GR, WA, and RE activities with an overall F1 performance score of 0.91, suggesting satisfactory application of the trained models to monitor cattle grazing activities on desert rangeland.
Forfattere
Ingeborg Callesen Marjo Palviainen Kęstutis Armolaitis Charlotte Rasmussen O. Janne KjønaasSammendrag
Purpose: Laser diffraction (LD) for determination of particle size distribution (PSD) of the fine earth fraction appeared in the 1990s, partly substituting the Sieving and Sedimentation Method (SSM). Whereas previous comparison between the two methods predominantly encompasses agricultural soils, less attention has been given to forest soils, including pre-treatment requirements related to their highly variable contents of carbon and Alox+ Feox. In this small collaborative learning study we compared (1) national SSM results with one type/protocol of LD analysis (Coulter), (2) LD measurements performed on three different LD instruments / laboratories, and (3) the replication error for LD Coulter analysis of predominantly sandy and loamy forest soils. Methods: We used forest soil samples from Denmark, Norway and Lithuania and their respective national SSM protocols / results. LD analyses were performed on Malvern Mastersizer 2000, Sympatec HELOS version 1999, and Coulter LS230, located at University of Copenhagen, Aarhus University and Helsinki University, respectively. The protocols differed between laboratories, including the use of external ultrasonication prior to LD analysis. Results: The clay and silt fractions content (<20 μm) from the LD analysis were not comparable with SSM results, with differences ranging from −0.5 to 22.3 percentage points (pp) for clay. Preliminary results from loamy samples with spodic material suggested inconsistent effects of external ultrasonication to disperse aggregates. The comparison between the three LD instruments showed a range in the clay and silt fractions content of 1.9–5.3 and 6.2–8.1 pp, respectively. Differences may be related to the instruments, protocols, and content of a given particle size fraction. The replication error of the Coulter LD protocol was found to be <3 pp in sandy soils, but up to 10 pp in loamy soils. Conclusion: Differences in the clay fraction results partly affected the classification of soil types. The fast replication of the LD analysis enables more quality control of results. The pedological evaluation of non-silicate constituents and optional pre-treatment steps (e.g., soil organic matter or sesquioxides) remains the same for LD and SSM. For comparison of results, detailed descriptions of the analytical protocol including pre-treatments are needed irrespective of instrument and theoretical approach.
Sammendrag
Information on tree height-growth dynamics is essential for optimizing forest management and wood procurement. Although methods to derive information on height-growth information from multi-temporal laser scanning data already exist, there is no method to derive such information from data acquired at a single point in time. Drone laser scanning data (unmanned aerial vehicles, UAV-LS) allows for the efficient collection of very dense point clouds, creating new opportunities to measure tree and branch architecture. In this study, we examine if it is possible to measure the vertical positions of branch whorls, which correspond to nodes, and thus can in turn be used to trace the height growth of individual trees. We propose a method to measure the vertical positions of whorls based on a single-acquisition of UAV-LS data coupled with deep-learning techniques. First, single-tree point clouds were converted into 2D image projections, and a YOLOv5 (you-only-look-once) convolutional neural network was trained to detect whorls based on a sample of manually annotated images. Second, the trained whorl detector was applied to a set of 39 trees that were destructively sampled after the UAV-LS data acquisition. The detected whorls were then used to estimate tree-, plot- and stand-level height-growth trajectories. The results indicated that 70 per cent (i.e. precision) of the measured whorls were correctly detected and that 63 per cent (i.e. recall) of the detected whorls were true whorls. These results translated into an overall root-mean-squared error and Bias of 8 and −5 cm for the estimated mean annual height increment. The method’s performance was consistent throughout the height of the trees and independent of tree size. As a use case, we demonstrate the possibility of developing a height-age curve, such as those that could be used for forecasting site productivity. Overall, this study provides proof of concept for new methods to analyse dense aerial point clouds based on image-based deep-learning techniques and demonstrates the potential for deriving useful analytics for forest management purposes at operationally-relevant spatial-scales.
Sammendrag
Supplemental feeding of cervids during winter is a widespread management practice, but feeding may increase the risk of disease transmission. Therefore, legal regulations to limit supplemental feeding are often implemented when dealing with severe infectious diseases, such as chronic wasting disease (CWD) in cervids. However, it is currently unclear whether these regulations result in decreased spatial clustering and aggregation as intended. Supplemental feeding is expected to restrict the movement of cervids. Therefore, a ban on feeding may also result in wider space use and a risk of geographic spread of disease. The space use of 63 GPS-marked red deer (Cervus elaphus) was investigated before (n = 34) and after (n = 29) the implementation of a legal regulation aimed at limiting the supplemental feeding of cervids during winter in a CWD-affected region of Nordfjella, Norway. Snow depth was the main determinant of the space use for red deer. A moderate reduction in the number of GPS positions in spatial clusters was evident during periods of deep snow once the ban was in place. Sizes of core areas (Kernel 50%), home ranges (Kernel 95%), and dispersion (MCP 100%, number of 1 km2 pixels visited per deer) declined from January to March and with increasing snow depth. Dispersion (number of 1 km2 pixels visited per deer) did not depend on snow depth after the ban, and red deer used larger areas when snow depth was high after the ban compared to before. The ban on supplementary feeding had no effect on size of core areas or home ranges. Several potential factors can explain the overall weak effect of the ban on space use, including the use of agricultural fields by red deer, other anthropogenic feeding, and landscape topography. This study highlights that snow depth is the main factor determining space use during winter, and it remains to be determined whether the moderate reduction in spatial clustering during deep snow after the ban was sufficient to lower the risk of disease transmission.
Forfattere
Milan Mataruga Branislav Cvjetković Bart De Cuyper Ina Aneva Petar Zhelev Pavel Cudlín Marek Metslaid Ville Kankaanhuhta Catherine Collet Peter Annighöfer Thomas Mathes Tsakaldimi Marianthi Paitaridou Despoina Rakel J. Jónsdóttir Maria Cristina Monteverdi Giovanbattista de Dato Barbara Mariotti Dana Dina Kolevska Jelena Lazarević Inger Sundheim Fløistad Marcin Klisz Wojciech Gil Vasco Paiva Teresa Fonseca Valeriu-Norocel Nicolescu Vladan Popović Jovana Devetaković Ivan Repáč Gregor Božič Hojka Kraigher Enrique Andivia Julio J. Diez Henrik Böhlenius Magnus Löf Nebi Bilir Pedro Villar-SalvadorSammendrag
The relationship between the quality of forest seedlings and their outplanting survival and growth has long been recognized. Various attributes have been proposed to measure the quality of planted seedlings in forest regeneration projects, ranging from simple morphological traits to more complex physiological and performance attributes, or a combination thereof. However, the utility and meaning of seedling quality attributes can differ significantly among regions, nursery practices, site planting conditions, species and the establishment purpose. Here, forest scientists compiled information using a common agreed questionnaire to provide a review of current practices, experiences, legislation and standards for seedling quality across 23 European countries. Large differences exist in measuring seedling quality across countries. The control of the origin of seed and vegetative material (genetic component of plant quality), and control of pests and diseases are common practices in all countries. Morphological attributes are widely used and mandatory in most cases. However, physiological attributes are hardly used at the operative level and mainly concentrated to Fennoscandia. Quality control legislation and seedling quality standards are less strict in northern European countries where seedling production is high, and quality control relies more on the agreements between producers and local plant material users. In contrast, quality standards are stricter in Southern Europe, especially in the Mediterranean countries. The control of seedling quality based on plantation and reforestation success is uncommon and depends on the conditions of the planting site, the traditional practices and the financial support provided by each country. Overall, European countries do not apply the “target seedling concept” for seedling production except for seed origin. Seedling production in many countries is still driven by traditional “know-how” and much less by scientific knowledge progress, which is not adequately disseminated and transferred to the end-users. Our review highlights the need for greater harmonization of seedling quality practices across Europe and the increased dissemination of scientific knowledge to improve seedling quality in forest regeneration activities.
Forfattere
Erlend Birkeland Nilsen Bjarne Olai Braastad Svein Dale Børre Kind Dervo Kyrre Linné Kausrud Lawrence Richard Kirkendall Martin Malmstrøm Cecilie Marie Mejdell Eli Knispel Rueness Paul Ragnar Berg Anders Bryn Katrine Eldegard Sonya Rita Geange Kjetil Hindar Anders Nielsen Brett Kevin Sandercock Eva Bonsak Thorstad Gaute VelleSammendrag
VKM has evaluated to what extent keeping of cats pose a risk to biodiversity in Norway. Risks were assessed separately for threats to biodiversity from direct predation, indirect (non-lethal) effects, competition with other wildlife and spread of infectious organisms. VKM also assessed the risk of reduced animal welfare related to the keeping of domestic cats, both for the cats and their prey. In addition, VKM has assessed a range of risk-reducing measures aimed at minimizing the risk for negative impacts on biodiversity and animal welfare. Overall, VKM find that the risk of negative impact on vulnerable birds and red-listed mammalian species are high under certain conditions. VKM also find that there is a considerable risk associated with increased spread of infectious organisms from cats to wildlife and other domestic species. Some of these infectious organisms may also infect humans. With respect to mitigation measures, VKM concludes that measures focused on limiting cats’ access to prey populations are likely to yield the most positive outcomes in terms of mitigating the adverse impact on biodiversity.