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
Sammendrag
Weeds affect crop yield and quality due to competition for resources. In order to reduce the risk of yield losses due to weeds, herbicides or non-chemical measures are applied. Weeds, especially creeping perennial species, are generally distributed in patches within arable fields. Hence, instead of applying control measures uniformly, precision weeding or site-specific weed management (SSWM) is highly recommended. Unmanned aerial vehicle (UAV) imaging is known for wide area coverage and flexible operation frequency, making it a potential solution to generate weed maps at a reasonable cost. Efficient weed mapping algorithms need to be developed together with UAV imagery to facilitate SSWM. Different machine learning (ML) approaches have been developed for image-based weed mapping, either classical ML models or the more up-to-date deep learning (DL) models taking full advantage of parallel computation on a GPU (graphics processing unit). Attention-based transformer DL models, which have seen a recent boom, are expected to overtake classical convolutional neural network (CNN) DL models. This inspired us to develop a transformer DL model for segmenting weeds, cereal crops, and ‘other’ in low-resolution RGB UAV imagery (about 33 mm ground sampling distance, g.s.d.) captured after the cereal crop had turned yellow. Images were acquired during three years in 15 fields with three cereal species (Triticum aestivum, Hordeum vulgare, and Avena sativa) and various weed flora dominated by creeping perennials (mainly Cirsium arvense and Elymus repens). The performance of our transformer model, 1Dtransformer, was evaluated through comparison with a classical DL model, 1DCNN, and two classical ML methods, i.e., random forest (RF) and k-nearest neighbor (KNN). The transformer model showed the best performance with an overall accuracy of 98.694% on pixels set aside for validation. It also agreed best and relatively well with ground reference data on total weed coverage, R2 = 0.598. In this study, we showed the outstanding performance and robustness of a 1Dtransformer model for weed mapping based on UAV imagery for the first time. The model can be used to obtain weed maps in cereals fields known to be infested by perennial weeds. These maps can be used as basis for the generation of prescription maps for SSWM, either pre-harvest, post-harvest, or in the next crop, by applying herbicides or non-chemical measures.
Sammendrag
Denne rapporten gir en oversikt over tilstanden i skog som var vernet per. 1.1.2021. Datamaterialet som er utgangspunktet for rapporten er registreringer gjennomført av Landsskogtakseringen, gjennom «Overvåkingsprogrammet for skog i verneområder». Registreringene er utført i løpet av femårsperioden 2017-2021. Utvalgte resultater: • Vernet skog omfattet per 1.1. 2021 totalt 592 481 ha, tilsvarende 4,9 prosent av det totale skogarealet. • 3,7 prosent av den produktive skogen, og 7,9 prosent av den uproduktive skogen i landet finnes i vernet skog, der skogbruk ikke er tillatt. • I produktiv skog er andelen skogareal i klassene middels og høy+ svært høy bonitet underrepresentert samlignet med skogen generelt. • Skogen i verneområder er generelt eldre og har en større andel skog i senere utviklingstrinn. Biologisk gammel skog etter Landsskogtakseringens definisjon utgjør nærmere tre ganger så høy andel i den produktive delen av vernet skogareal som i produktiv skog totalt. • Det stående volumet i verneområdene utgjør 4,1 prosent av totalt stående volum. • Gjennomsnittlig tilvekst i skog som var vernet per 1.1.2016 er lavere enn gjennomsnittet for skog generelt. • Vernet skog inneholder mer volum død ved per hektar i gjennomsnitt enn øvrig skog. • I produktiv skog er MiS-livsmiljøene “liggende dødved” og “stående dødved”, samt “gamle trær” vanligere i verneområdene. For uproduktiv skog er “gamle trær” vanligere. I tillegg presenteres resultater som viser hvordan den vernede skogen har utviklet seg siden forrige taksering, som ble gjennomført 2012-2016.
Sammendrag
Vipe (Vanellus vanellus) har de siste tiårene hatt en sterk nedgang i bestanden. Statsforvalteren i Rogaland innførte tiltaket ‘vipestriper’ i Time kommune i 2019 og for hele fylket i 2020, som del av RMP. Målsetningen for dette prosjektet har vært å evaluere bruk og effekt av vipestriper, og finne ut hvorvidt stripene oppleves som et vellykket tiltak for å ta vare på vipa i jordbrukslandskapet. Vi har gjennomført en spørreundersøkelse og arrangert et folkemøte med gårdbrukere som har etablert vipestriper eller som har vist interesse for disse. Resultatene er basert på svarene til de 40 deltakerne som gjennomførte spørreundersøkelsen, samt samtaler under folkemøtet og tilbakemeldinger via e-post. Vi konkluderer med at vipestriper generelt har en positiv effekt, som varierer noe avhengig av omkringliggende arealer. Vi anbefaler at tiltaket videreføres med følgende hensyn: Vipestriper bør anlegges særlig der fuglene hekker jevnlig, og i nærheten av våte arealer. Vipestriper bør ikke anlegges nærmere enn 50 m fra høye busker og heller ikke på høstsådd areal. Turgåere bør kanaliseres vekk fra vipestriper og andre områder med mye vipe i hekkesesongen.
Forfattere
Martina Paponov Jörg Ziegler Ivan PaponovSammendrag
Light acts as a trigger to enhance the accumulation of secondary compounds in the aboveground part of plants; however, whether a similar triggering effect occurs in roots is unclear. Using an aeroponic setup, we investigated the effect of long term exposure of roots to LED lighting of different wavelengths on the growth andp hytochemical composition of two high-value medicinal plants, Artemisia annua and Hypericum perforatum. In A. annua, root exposure to white, blue, and red light enhanced the accumulation of artemisinin in the shoots by 2.3-, 2.5-, and 1.9-fold, respectively. In H. perforatum, root exposure to white, blue, red, and green light enhanced the accumulation of coumaroylquinic acid in leaves by 89, 65, 84, and 74%, respectively. Root lighting also increased flavonol concentrations. In contrast to its effects in the shoots, root illumination did not change phytochemical composition in the roots or root exudates. Thus, root illumination induces a systemic response, resulting in modulation of the phytochemical composition in distal tissues remote from the light exposure site.
Redaktører
Giuseppe E. Scarascia-Mugnozza Vicente Guallart Fabio Salbitano Giovanna Ottaviani Aalmo Stefano BoeriSammendrag
This edited volume centers around the concept of BioCities, which aim to unify nature and urban spaces in order to reverse the effects of global climate change and inequity. Following this principle, the authors propose multiple approaches for sustainable city growth. The discussed concepts are not only relevant for newly constructed cities, but offer transformative perspectives for existing settlements as well. Placing nature at the forefront of city planning is not an entirely new concept, so the authors build on established ideas like the garden city, green city, eco-city, or smart city. All chapters aim to highlight aspects to develop a city that is a resilient nature-based socio-ecological system. Many of these concepts were formed in an effort to copy the best traits of a forest ecosystem: a home for many different species that build complex communities. Much like many of our forests, urban areas are managed by humans for multifunctional purposes, using living and abiotic components. This viewpoint helps to understand the potential and limitations of sustainable growth. With these chapters, the authors want to inspire planners, ecologists, urban foresters and decision makers of the future.
Forfattere
Yi Zhang Yijing Feng Zhonghao Ren Runguo Zuo Tianhui Zhang Yeqing Li Yajing Wang Zhiyang Liu Ziyan Sun Yongming Han Lu Feng Mortaza Aghbashlo Meisam Tabatabaei Junting PanSammendrag
The ideal conditions for anaerobic digestion experiments with biochar addition are challenging to thoroughly study due to different experimental purposes. Therefore, three tree-based machine learning models were developed to depict the intricate connection between biochar properties and anaerobic digestion. For the methane yield and maximum methane production rate, the gradient boosting decision tree produced R2 values of 0.84 and 0.69, respectively. According to feature analysis, digestion time and particle size had a substantial impact on the methane yield and production rate, respectively. When particle sizes were in the range of 0.3–0.5 mm and the specific surface area was approximately 290 m2/g, corresponding to a range of O content (>31%) and biochar addition (>20 g/L), the maximum promotion of methane yield and maximum methane production rate were attained. Therefore, this study presents new insights into the effects of biochar on anaerobic digestion through tree-based machine learning.
Sammendrag
Artificial freezing tests were performed on seedlings from Norway spruce families at the end of the first growing season. Similar tests were made on twigs collected from trees in a progeny test at the end of growing season nine. The 26 families in the early test were included in the short-term progeny test with 100 full-sib families from a 10 x 10 factorial cross. All families were also planted in seven field trials in Norway, Sweden and Finland, from which data on mortality, tree heights and stem damage at age 10 years are available. Significant difference was found among families for freezing test injuries on whole intact seedlings at the end of the first growing season and for lethal temperature of needles on detached twigs collected at the end of growing season nine. However, no relationships were found between the freezing test scores of families in the two types of tests or few between these scores and the traits measured in the short-term and field trials. The results show that frost hardiness testing of families at a young age, grown under artificial temperature and light conditions in nursery, is a weak predictor of their performance under natural conditions in field at older ages.
Forfattere
Ana Vuković Vimić Mirjam Vujadinović Mandić Milica Fotirić Akšić Ksenija Vukićević Mekjell MelandSammendrag
Agricultural production is already, and obviously, affected by climate change. Adapting to climate change includes reducing future risks to ensure yield quality and quantity and considers seizing any potential opportunities induced by climate change. In higher latitude areas, such as Norway, cold climate limits the cultivation of fruits. An increase in temperature offers more favorable conditions for fruit production. In this study, using available phenological observations (full blooming) and harvest dates, and meteorological data from the experimental orchard of NIBIO Ullensvang, the minimum heat requirements for growing different apple varieties are determined. Those criteria are used for zoning of the areas with heat favorable conditions for apple growing. Data on six varieties were used, with lower and higher requirements for heat for fruit development (Discovery, Gravenstein, Summerred, Aroma, Rubinstep, and Elstar). High resolution daily temperature data were generated and used for zoning of the areas with heat favorable conditions for apple growing within the selected domain, which includes Western Norway, Southern Norway, Eastern Norway, and the western part of Trøndelag, Mid-Norway. Dynamics of the change in such surfaces was assessed for the period of 1961–2020. The total surface with favorable heat conditions for growing the varieties with lesser requirement for heat increased three times during this period. The growing of more heat-demanding varieties increased from near zero to about 2.5% of the studied land surface. In the period of 2011–2020, surface area with favorable heat conditions for apple growing was almost 27,000 km2, and a surface area of about 4600 km2 can sustain growing of more heat-demanding varieties. The presented results show the increasing potential of the climate of Norway for apple cultivation and highlight the importance of implementation of fruit production planned according to climate change trends, including the assessment of potential risks from climate hazards. However, the methodology for determining heat requirements can be improved by using phenological ripening dates if available, rather than harvest dates which are impacted by human decision. Zoning of areas with the potential of sustainable apple growing requires the use of future climate change assessments and information on land-related features.
Sammendrag
Wetlands are simply areas that are fully or partially saturated with water. Not much attention has been given to wetlands in the past, due to the unawareness of their value to the general public. However, wetlands have numerous hydrological, ecological, and social values. They play an important role in interactions among soil, water, plants, and animals. The rich biodiversity in the vicinity of wetlands makes them invaluable. Therefore, the conservation of wetlands is highly important in today’s world. Many anthropogenic activities damage wetlands. Climate change has adversely impacted wetlands and their biodiversity. The shrinking of wetland areas and reducing wetland water levels can therefore be frequently seen. However, the opposite can be seen during stormy seasons. Since wetlands have permissible water levels, the prediction of wetland water levels is important. Flooding and many other severe environmental damage can happen when these water levels are exceeded. Therefore, the prediction of wetland water level is an important task to identify potential environmental damage. However, the monitoring of water levels in wetlands all over the world has been limited due to many difficulties. A Scopus-based search and a bibliometric analysis showcased the limited research work that has been carried out in the prediction of wetland water level using machine-learning techniques. Therefore, there is a clear need to assess what is available in the literature and then present it in a comprehensive review. Therefore, this review paper focuses on the state of the art of water-level prediction techniques of wetlands using machine-learning techniques. Nonlinear climatic parameters such as precipitation, evaporation, and inflows are some of the main factors deciding water levels; therefore, identifying the relationships between these parameters is complex. Therefore, machine-learning techniques are widely used to present nonlinear relationships and to predict water levels. The state-of-the-art literature summarizes that artificial neural networks (ANNs) are some of the most effective tools in wetland water-level prediction. This review can be effectively used in any future research work on wetland water-level prediction.
Forfattere
Jorge Aldea Miren del Rio Nicolas Cattaneo José Riofrío Cristóbal Ordóñez Sara Uzquiano Felipe BravoSammendrag
Thinning treatments along with the establishment of mixed forest stands have been put forward as possible adaptation strategies to cope with climate change, although the effectiveness of combining these two measures has scarcely been studied and may vary depending on stand conditions and the thinning regime employed. The aim of this study was to better understand the effect of commercial thinning and of the different growth behavior of two coexisting species on their inter- and intra-annual cumulative radial increment patterns. For this purpose, we studied radial increment in a Scots pine-Pyrenean oak (Pinus sylvestris L.-Quercus pyrenaica Willd.) Mediterranean mixed forest in north-west Spain over two climatically contrasting years (2016–2017). The data came from a thinning trial consisting of a randomized latin square design with a control and two commercial thinning treatments from below; one moderate and the other heavy, removing 25% and 50 % of initial basal area, respectively, of both species. The radial increment was analyzed based on bi-weekly readings from band dendrometers installed on 90 oak and pine trees. A non-linear mixed model based on double-Richards curve was fitted to explore the differences between thinning treatments and species response in the intra-annual cumulative radial increment patterns. Inter-annual basal area increments for each species at stand level were quantified by aggregating the tree estimates obtained from the model fitted in the first step. Tree and stand level growth were greater in Scots pine, which also showed a greater growth response to early spring droughts than the Pyrenean oak. Heavy thinning increased radial increment in trees of both species at the expense of decreased total stand basal area. At species level, basal area growth in Scots pine decreased through thinning, whereas for Pyrenean oak, the heavy thinning intensity resulted in the same basal area growth as the control. Thus, heavy thinning induced a trade-off between total stand growth and tree-level response to climatic conditions for Scots pine but with no loss in productivity in the case of the Pyrenean oak. Hence, heavy thinning may be an appropriate measure to attain productive stability of the oak coppice in the studied mixed forest as well as to adapt tree growth to future droughts associated with climate change.