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.
2025
Sammendrag
1. Field-based vegetation mapping is important for environmental assessments.Often, the area covered by a species is estimated visually within a reference frame.However, such assessments are prone to observer bias and a large variability. 2. We developed a deep learning pipeline relying on YOLOv8 models to segmentspecies and estimate the percentage cover (%) of Vaccinium myrtillus (blueberry)and Vaccinium vitis-idaea (lingonberry), two key understory species in borealforests. We used 138 nadir and downward-looking images of the forest floorcaptured in correspondence with 50 × 50 cm vegetation sub-plots assessedwithin National Forest Inventory (NFI) plots. First, we trained a bounding-boxframe detection model to crop the image to the same area assessed in the field.Second, we trained an instance segmentation model to classify species. Third,we flattened the class values into a semantic raster and estimated the species-specific cover by pixel counting. 3. We evaluated our method against an independent test set of 156 images andfound a root mean squared error (RMSE) of 8.82% for blueberry and 3.49% forlingonberry and no substantial systematic errors. An additional comparison withocular estimation by various field workers for the same plots showed that themodel estimates were within the range of estimates by field workers 8 out of 9times for blueberry and 7 out of 9 times for lingonberry. 4. The developed method shows promise in reducing observer bias and variabilityin vegetation surveys, thereby improving their consistency while significantlyreducing the time needed for species-specific coverage estimation. This isparticularly beneficial for repeated measurements and monitoring vegetationcover dynamics. However, as the method relies on RGB data, it is limited toestimating the percentage of visible species that are not obscured by others.Expanding the method to include a broader range of cover classes (e.g. grasses,rocks, logs) or species could automate the capture of crucial information
Forfattere
Ararsa Derese Seboka Lu Feng John Morken Muyiwa S. Adaramola Getachew Birhanu Abera Gebresilassie Asnake EwunieSammendrag
The growing hotel and education sectors in Ethiopia face increasing waste and energy demands, necessitating effective waste management and energy use strategies. This study is aimed to investigates biowaste production and energy consumption in hotels and university campuses in Southern Ethiopia, focusing on sustainable solutions for reducing environmental impacts. A mixed-methods approach, including surveys and onsite measurements, were used to assess energy consumption, biowaste generation, and management practices. A stratified purposive sampling was employed to select institutions, and both descriptive and inferential statistics, including time series analysis, multiple regression models, were applied; the environmental footprint of energy sources and energy potentials of biowastes were quantified following the guidelines set by the Intergovernmental Panel on Climate Change (IPCC).The study found that the primary energy sources for both sectors are electricity, natural gas/LPG, diesel fuel, fuelwood, and charcoal, with electricity being the dominant source. Hotels exhibit a consistent increase in energy consumption from 2016 to 2023, driven by tourism and service expansion, while university campuses show more fluctuating trends influenced by student enrollment and policy changes. Both sectors generate substantial biowaste annually—over 588 tons from hotels and 1448 tons from campuses—comprising food, fruit, vegetable and animal waste. However, waste management practices are often inadequate, with open dumping being common and the lack of energy recovery or treatment systems. The study quantified the greenhouse gas (GHG) emissions, found that non-electric energy sources such as oil fuels and firewood contribute significantly to CO2 emissions. In 2023, oil fuels accounted for 15,474.2 tonnes of CO2e, and firewood generated 130,377.2 tonnes CO2e, highlighting the need for cleaner energy alternatives to reduce emissions and reliance on carbon intensive energy sources.
Forfattere
Adrian Unc Majdi R. Abou Najm Paul Eric Aspholm Tirupati Bolisetti Colleen Charles Ranjan Datta Trine Eggen Belinda Eline Flem Getu Hailu Eldbjørg Sofie Heimstad Margot Hurlbert Meriam Karlsson Marius Støylen Korsnes Arthur Nash David Parsons Radha Sivarajan Sajeevan Narasinha J. Shurpali Govert Valkenburg Danielle Wilde Bing Wu Sandra F. Yanni Debasmita MisraSammendrag
Arctic food systems blend Traditional Ecological Knowledge with modern, often energy-intensive influences, triggered by colonization. Food systems’ future depends on alignment of tradition with innovation, facilitation of resilience and a heritage-driven interaction with the global economy – at a pace determined by local communities.
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Small, forested catchments are prototypes of terrestrial ecosystems and have been studied in several disciplines of environmental science over several decades. Time series of water and matter fluxes and nutrient concentrations from these systems exhibit a bewildering diversity of spatiotemporal patterns, indicating the intricate nature of processes acting on a large range of time scales. Nonlinear dynamics is an obvious framework to investigate catchment time series. We analyzed selected long-term data from three headwater catchments in the Bramke valley, Harz mountains, Lower Saxony in Germany at common biweekly resolution for the period 1991 to 2023. For every time series, we performed gap filling, detrending, and removal of the annual cycle using singular system analysis (SSA), and then calculated metrics based on ordinal pattern statistics: the permutation entropy, permutation complexity, and Fisher information, as well as their generalized versions (q-entropy and α-entropy). Further, the position of each variable in Tarnopolski diagrams is displayed and compared to reference stochastic processes, like fractional Brownian motion, fractional Gaussian noise, and β noise. Still another way of distinguishing deterministic chaos and structured noise, and quantifying the latter, is provided by the complexity from ordinal pattern positioned slopes (COPPS). We also constructed horizontal visibility graphs and estimated the exponent of the decay of the degree distribution. Taken together, the analyses create a characterization of the dynamics of these systems which can be scrutinized for universality, either across variables or between the three geographically very close catchments.