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
Forfattere
Alexander Oliver Jüterbock Hin Hoarau Heemstra Karin Andrea Wigger Bernardo Duarte Christian Guido Bruckner Annelise Chapman Delin Duan Aschwin Engelen Clement Gauci Griffin Goldstein Hill Zi-Min Hu Prabhat Khanal Ananya Khatei Amy Leigh Mackintosh Heidi Meland Ricardo Melo Anne Margrete Leiros Nilsen Leonore Olsen Ralf Rautenberger Henning Reiss Jie ZhangSammendrag
How to build a sustainable seaweed industry is important in Europe’s quest to produce 8 million tons of seaweed by 2030. Based on interviews with industry representatives and an expert-workshop, we developed an interdisciplinary roadmap that addresses sustainable development holistically. We argue that sustainable practices must leverage synergies with existing industries (e.g. IMTA systems, offshore wind farms), as the industry develops beyond experimental cultivation towards economic viability.
Forfattere
Tatsiana Espevig Kristine Sundsdal Victoria Stornes Moen Ramsøy Kate Entwistle Marina Usoltseva Sabine Braitmaier Daniel Hunt Carlos Guerrero Monica Skogen Erik LysøeSammendrag
Thirty-seven turfgrass samples expressing dollar spot symptoms were collected in summer 2020 on golf courses in Sweden, Denmark, United Kingdom, Germany, Portugal, and Spain. The fungi were isolated at Norwegian Institute of Bioeconomy Research (NIBIO) Turfgrass Laboratory (Norway) and sent for molecular identification using sequencing of regions of ITS (internal transcribed regions of the ribosomal DNA) and calmodulin. Clarireedia homoeocarpa was identified in four turfgrass samples and Clarireedia jacksonii was identified in 11 turfgrass samples. From seven turfgrass samples, the isolated fungi were not Clarireedia spp., but Waitea circinata, Fusarium culmorum, and Fusarium oxysporum. This suggests dollar spot is not always accurately identified from foliar symptoms in the field.
Sammendrag
This article presents a novel, ultralight tree planting mechanism for use on an aerial vehicle. Current tree planting operations are typically performed manually, and existing automated solutions use large land-based vehicles or excavators which cause significant site damage and are limited to open, clear-cut plots. Our device uses a high-pressure compressed air power system and a novel double-telescoping design to achieve a weight of only 8 kg: well within the payload capacity of medium to large drones. This article describes the functionality and key components of the device and validates its feasibility through experimental testing. We propose this mechanism as a cost-effective, highly scalable solution that avoids ground damage, produces minimal emissions, and can operate equally well on open clear-cut sites as in denser, selectively-harvested forests.
Forfattere
Ellen Johanne Svalheim Bolette Bele Bjørn Egil Flø Elin Blütecher Synnøve Grenne Marie Uhlen Maurset Pål ThorvaldsenSammendrag
Det er ikke registrert sammendrag
Forfattere
Anne MuolaSammendrag
Det er ikke registrert sammendrag
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Anne MuolaSammendrag
Det er ikke registrert sammendrag
Forfattere
Lucas K. Johnson Zhiqiang Yang Angela Erb Ryan Bright Grant M. Domke Tracey S. Frescino Crystal B. Schaaf Sean P. HealeySammendrag
Reforestation is generally regarded as having the most substantial climate mitigation potential among a suite of available natural climate solutions which have focused almost exclusively on the benefits of carbon sequestration and storage. However, these reforestation studies have not accounted for the adverse warming impacts resulting from corresponding surface albedo change. A newly available dataset developed with albedo imagery from the Landsat 8 satellite analyzed at field plots from the United States (US) Forest Inventory and Analysis (FIA) program provides non-soil carbon stocks and corresponding carbon-equivalent albedo offsets for 30 distinct forest-type groups indexed by 10-year age bins. In this case study we leverage this new dataset in concert with FIA species distribution data to investigate reforestation scenario planning based on joint carbon-albedo estimates (non-soil carbon stock less a carbon-equivalent albedo offset) instead of just carbon storage estimates alone. Specifically, our analysis informs managers interested in planting optimal forest-type groups for climate change mitigation outcomes approaching the year 2050. We assist in one of the most fundamental steps in any reforestation project: deciding which forest type or tree species mix to plant. We present our results as forest-type group recommendations within 64,000 hectare hexagons as a means to offer localized guidance and to examine the spatial patterns of albedo impacts across the conterminous US. We found that albedo offsets were most impactful on decisions in the Northeastern regions of the US, where optimizing for joint carbon-albedo in the next 25-years implies planting deciduous forest-type groups (Maple/beech/birch) instead of otherwise carbon-optimal coniferous forest-type groups (White/red/jack pine). Although the consideration of albedo did not alter 25-year tree planting decisions in most of the US, it did reduce the expected climate benefit of reforestation in general. We provide a standalone application that ranks all forest-type groups detected by FIA within a given hexagon, allowing managers to evaluate alternatives in light of site-specific constraints. This paper describes a replicable case study for incorporating albedo offsets in reforestation plans. Similar analyses may be performed anywhere Landsat albedo data are available over adequate measurements of forest carbon stocks. Recommendations: • Albedo impacts on 25-year tree planting decisions are concentrated in the Northeastern regions of the United States, where considering albedo offsets together with carbon stocks implies planting the Maple/beech/birch forest-type group in place of the otherwise carbon-optimal White/red/jack pine group. • Our reforestation support application allows managers to explore localized forest-type group rankings on the basis of joint carbon-albedo benefits. • Fine-resolution albedo data, which is not currently a standard data product, provides more comprehensive support for reforestation projects intended to mitigate global climate change.
Forfattere
Jari Hynynen Narayanan Subramanian Clara Antón Fernandéz Soili Haikarainen Emma Holmström Micky Allen Saija Huuskonen Jouni Siipilehto Hannu Salminen Mika Lehtonen Kjell Andreassen Urban NilssonSammendrag
We studied the ability of extended rotations as a measure to promote sustainable management ofproduction forests in Nordic countries. We carried out scenario analyses for three large forestregions in Southern Finland, Central Sweden, and South-Eastern Norway, where forestry has a highsocioeconomic value. We analyzed the effects on wood production, carbon sequestration, and theamount of produced deadwood over the 50 years. In the reference scenario (BAU), the prevailingmanagement of production forests was applied. In the scenario for extended rotations (EXT),rotation lengths were extended by 30 years, on average. We used data from national forestinventories to represent the current stage of the regions’ forests and produced future forecastsusing local models, which have been widely applied in large-scale analyses. The increase in carbonsequestration and production of deadwood in production forests can be achieved by lengtheningrotations but only at the expense of harvesting removals. The increase in annual carbonsequestration is between 0.7 and 1.6 Mg CO2 eq ha−1. Natural mortality increases by 20–30% alongwith the amount of deadwood by 0.15 m3 ha−1 a−1, on average. The decrease in the mean annualharvesting removals varies from 0.4 to 1.6 m3 ha−1 a−1 from region to region.
Forfattere
Andreas Hagenbo Lise Dalsgaard Marius Hauglin Stephanie Eisner Line Tau Strand O. Janne KjønaasSammendrag
Boreal forest soils are a critical terrestrial carbon (C) reservoir, with soil organic carbon (SOC) stocks playing a key role in global C cycling. In this study, we generated high-resolution (16 m) spatial predictions of SOC stocks in Norwegian forests for three depth intervals: (1) soil surface down to 100 cm depth, (2) forest floor (LFH layer), and (3) 0–30 cm into the mineral soil. Our predictions were based on legacy soil data collected between 1988 and 1992 from a subset (n = 1014) of National Forest Inventory plots. We used boosted regression tree models to generate SOC estimates, incorporating environmental predictors such as land cover, site moisture, climate, and remote sensing data. Based on the resulting maps, we estimate total SOC stocks of 1.57–1.87 Pg C down to 100 cm, with 0.55–0.66 Pg C stored in the LFH layer and 0.68–0.80 Pg C in the upper mineral soil. These correspond to average SOC densities of 15.3, 5.4, and 6.6 kg C m−2, respectively. We compared the predictive performance of these models with another set, supplemented by soil chemistry variables. These models showed higher predictive performance (R2 = 0.65–0.71) than those used for mapping (R2 = 0.44–0.58), suggesting that the mapping models did not fully capture environmental variability influencing SOC stock distributions. Within the spatial predictive models, Sentinel-2 Normalized Difference Vegetation Index, depth to water table, and slope contributed strongly, while soil nitrogen and manganese concentrations had major roles in models incorporating soil chemistry. Prediction uncertainties were related to soil depth, soil types, and geographical regions, and we compared the spatial prediction against external SOC data. The generated maps of this offer a valuable starting point for identifying forest areas in Norway where SOC may be vulnerable to climate warming and management-related disturbances, with implications for soil CO2 emissions.