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.
2024
Sammendrag
Lingonberry (Vaccinium vitis-idaea L.) grows in a range of nature types in the boreal zone, and understanding factors affecting the abundance of the plant, as well as mapping its spatial distribution, is important. The abundance of the species can be an indicator of ecosystem changes, and lingonberry can also be a source for commercial utilisation of berry resources. Using country-wide data from 6404 field plots of the Norwegian national forest inventory (NFI), we modelled the relationship between lingonberry cover and airborne laser scanning (ALS) and satellite metrics and bioclimatic variables describing the forest structure, terrain, soil properties and climate using a generalised mixed-effects model with a quasipoisson distribution. The validation carried out with an independent set of 2124 NFI plots indicated no obvious bias in predictions. The most important predictors were found to be interactions between dominant tree species, stand basal area and latitude, as well as the reflectance in the near-infrared band from Sentinel-2 satellite imagery, the dominant height based on the ALS variable and the long-term mean summer (June–August) temperature. The results provide an indicator of the effects of global warming, as well as the possibility of giving forest management prescriptions that favour lingonberry and locating the most abundant lingonberry sites in Norwegian forests.
Sammendrag
Red fescue (Festuca rubra L.) is the preferred turfgrass species for low-input golf course putting greens in Northern Europe. While it is well recognized that fescue requires less fertilizer than bentgrasses (Agrostis spp.) or annual bluegrass (Poa annua L.), the optimal fertilizer distribution throughout the growing season has not been investigated. Our objective was to determine the effects of three seasonal fertilizer distributions on turfgrass quality, seasonal growth rates, root development, and competition from annual bluegrass on a sand-based red fescue putting green at the NIBIO (Norwegian Institute of Bioeconomy Research) Turfgrass Research Center, Landvik, Norway (58° N). All fertilizer treatments comprised weekly inputs of a complete, liquid fertilizer solution for a total of 11 g N m−2 year−1, but the inputs were distributed with (1) the highest weekly rates from early May to mid-summer (SPRING+), (2) equal weekly rate from early May through late September (FLAT), or (3) the highest weekly rates from mid-August to late September (FALL+). SPRING+ fertilization resulted in higher turfgrass quality, deeper roots, and, in the second experimental year, less annual bluegrass than FALL+ fertilization. The advantage of FALL+ fertilization was faster green-up and enhanced growth in September, October, and April, but this came at the expense of more annual bluegrass. Results are discussed in light of previously published data on temperature and fertilizer requirements for the growth of red fescue versus annual bluegrass.
Forfattere
Sonja Keel Alice Budai Lars Elsgaard Brieuc Hardy Florent Levasseur Zhi Liang Claudio Mondini Cesar Plaza Jens LeifeldSammendrag
To increase soil organic carbon (SOC) storage, we need to improve our understanding on how to make best use of available plant biomass. Is it better to leave harvest residues on the field, or can we achieve higher SOC storage after processing biomass through, for instance, composting or pyrolysis to produce biochar? In the present study, we developed new parameters for different types of exogenous organic materials (EOMs), which allowed us to estimate the long-term effect of EOM addition on SOC storage using the soil carbon model RothC. For this purpose, we used a model version that included two additional EOM pools. First, we simulated the SOC evolution after addition of equal amounts of C in plant material and different EOMs (manure, compost, digestate, biochar) for a 38-year cropland trial in Switzerland. As expected, biochar showed the greatest increase in SOC due to its high stability. Next, we estimated how much C would remain after subjecting equivalent amounts of plant material and other EOMs to different processes. Loss rates of C for different processes were obtained from the literature. Due to different decomposition rates, the amounts of C remaining in the EOMs ranged from 7 % for anaerobic digestion of animal excreta to 100 % for plant material added directly to soil. These amounts of C were then added to the soil in the model experiments. Although the largest amount of C is lost during processing to biochar, biochar would clearly lead to highest long-term SOC stocks. Based on these first results we conclude that the trade-off between off-site stabilization and in-soil mineralization does not compromise the use of biochar for soil C storage. This means that despite the high C losses of about 50 % during biochar production, higher amounts of C remain in the soil because biochar has very low decomposition rates. In terms of C sequestration efficiency, biochar thus clearly outperforms the other biomass processing pathways. However, for practical recommendations, additional factors should be considered, such as nutrient availability of EOMs and environmental effects during processing, storage and soil application like nutrient leaching or gaseous emissions. Furthermore, we suggest a full life cycle assessment that considers e.g. energy costs for transport of biomass and energy savings from fossil fuel substitution by natural gas.
Forfattere
Johan Asplund Jenni Nordén O. Janne Kjønaas Rieke Lo Madsen Lisa Fagerli Lunde Tone Birkemoe Eivind Kverme Ronold Milda Norkute Ulrika Jansson Damian Petkovic Karlsen Anne Sverdrup-Thygeson Inger Skrede Ine-Susanne Hopland Methlie Sundy Maurice Ulrik Geiran Botten Regine Jusnes Krok Håvard Kauserud Line NybakkenSammendrag
The history of forestry in Fennoscandia spans five centuries, with clear-cutting being the dominant practice since the mid-20th century. This has led to a significant transformation of the forest landscape. In this study we investigated long-term effects of clear-cutting on forest structure and dead wood volumes. We established twelve pairs of spruce forest sites in southeastern Norway, each pair constituting of a mature, previously clear-cut stand and its near-natural counterpart with similar edaphic factors. The near-natural stands had 2.8 times higher volumes of dead wood and a larger proportion of dead wood in late stages of decay. The near-natural stands had on average 36.8 ± 9.1 m3 ha−1 of downed dead wood and 24.1 ± 6.2 m3 ha−1 of standing dead wood. Corresponding numbers for the previously clear-cut stands were 10.2 ± 2.8 m3 ha−1 and 11.9 ± 3.7 m3 ha−1. Forests with lower volumes of dead wood often also had lower connectivity of old spruce forests, which potentially have further negative effects on biodiversity. Furthermore, near-natural stands displayed greater tree size heterogeneity, resulting in a wider variation in light conditions. While no difference was observed in living tree volume, we found only weak evidence for higher basal area in the previously clear-cut stands, which had a higher stem density with more slender stems and shorter crowns. Our findings suggest that managed forests do not develop structures typical of near-natural forests before they become mature for logging. We stress the importance of a thorough site selection for studies of management effects, as forest management history may be confounded with productivity and other edaphic factors. Experimental designs like ours are vital for testing how differences in structure and deadwood volumes, driven by forest management, translate into variations in biodiversity, carbon sequestration and ecosystem functioning in future studies.
Forfattere
Alice Budai Daniel Rasse Thomas Cottis Erik J. Joner Vegard Martinsen Adam O'Toole Hugh Riley Synnøve Rivedal Ievina Sturite Gunnhild Søgaard Simon Weldon Samson ØpstadSammendrag
Carbon content is a key property of soils with importance for all ecosystem functions. Measures to increase soil carbon storage are suggested with the aim to compensate for agricultural emissions. In Norway, where soils have relatively high carbon content because of the cold climate, adapting management practices that prevent the loss of carbon to the atmosphere in response to climate change is also important. This work presents an overview of the potential for carbon sequestration in Norway from a wide range of agricultural management practices and provides recommendations based on certainty in the reported potential, availability of the technology, and likelihood for implementation by farmers. In light of the high priority assigned to increased food production and degree of self-sufficiency in Norway, the following measures were considered: (1) utilization of organic resources, (2) use of biochar, (3) crop diversification and the use of cover crops, (4) use of plants with larger and deeper root systems, (5) improved management of meadows, (6) adaptive grazing of productive grasslands (7) managing grazing in extensive grasslands, (8) altered tillage practices, and (9) inversion of cultivated peat with mineral soil. From the options assessed, the use of cover crops scored well on all criteria evaluated, with a higher sequestration potential than previously estimated (0.2 Mt CO2-equivalents annually). Biochar has the largest potential in Norway (0.9 Mt CO2-equivalents annually, corresponding to 20% of Norwegian agricultural emissions and 2% of total national emissions), but its readiness level is not yet achieved despite interest from industry to apply this technology at large scale. Extensive grazing and the use of deep-rooted plants also have the potential for increasing carbon storage, but there is uncertainty regarding their implementation and the quantification of effects from adapting these measures. Based on the complexities of implementation and the expected impacts within a Norwegian context, promising options with substantial payoff are few. This work sheds light on the knowledge gaps remaining before the presented measures can be implemented.
Sammendrag
This study focuses on advancing individual tree crown (ITC) segmentation in lidar data, developing a sensor- and platform-agnostic deep learning model transferable across a spectrum of dense laser scanning datasets from drone (ULS), to terrestrial (TLS), and mobile (MLS) laser scanning data. In a field where transferability across different data characteristics has been a longstanding challenge, this research marks a step towards versatile, efficient, and comprehensive 3D forest scene analysis. Central to this study is model performance evaluation based on platform type (ULS vs. MLS) and data density. This involved five distinct scenarios, each integrating different combinations of input training data, including ULS, MLS, and their augmented versions through random subsampling, to assess the model's transferability to varying resolutions and efficacy across different canopy layers. The core of the model, inspired by the PointGroup architecture, is a 3D convolutional neural network (CNN) with dedicated prediction heads for semantic and instance segmentation. The model underwent comprehensive validation on publicly available, machine learning-ready point cloud datasets. Additional analyses assessed model adaptability to different resolutions and performance across canopy layers. Our results reveal that point cloud random subsampling is an effective augmentation strategy and improves model performance and transferability. The model trained using the most aggressive augmentation, including point clouds as sparse as 10 points m−2, showed best performance and was found to be transferable to sparse lidar data and boosts detection and segmentation of codominant and dominated trees. Notably, the model showed consistent performance for point clouds with densities >50 points m−2 but exhibited a drop in performance at the sparsest level (10 points m−2), mainly due to increased omission rates. Benchmarking against current state-of-the-art methods revealed boosts of up to 20% in the detection rates, indicating the model's superior performance on multiple open benchmark datasets. Further, our experiments also set new performance baselines for the other public datasets. The comparison highlights the model's superior segmentation skill, mainly due to better detection and segmentation of understory trees below the canopy, with reduced computational demands compared to other recent methods. In conclusion, the present study demonstrates that it is indeed feasible to train a sensor-agnostic model that can handle diverse laser scanning data, going beyond current sensor-specific methodologies. Further, our study sets a new baseline for tree segmentation, especially in complex forest structures. By advancing the state-of-the-art in forest lidar analysis, our work also lays the foundation for future innovations in ecological modeling and forest management.
Sammendrag
The evolution of soil structure in agricultural soils is driven by natural and anthropogenic factors including inherent soil properties, climate and soil management interventions, all acting at different spatial and temporal scales. Although the causal relationships between soil structure and these individual factors are increasingly understood, their relative importance and complex interactive effects on soil structure have so far not been investigated across a geo-climatic region. Here we present the first attempt to identify the relative importance of factors that drive the evolution of soil structure in agricultural soils as well as their direction of effect with a focus on the temperate-boreal zone. This was done using a random forest (RF) approach including soil, climate, time, and site factors as covariates. Relative entropy, as quantified by the Kullback-Leibler (KL) divergence, was used as a quantitative index of soil structure, which is derived from the particle-size distribution and soil water retention data, and integrates the effects of soil structure on pores from the micrometre-scale to large macropores. Our dataset includes 431 intact topsoil and subsoil samples from 89 agricultural sites across Sweden and Norway, which were sampled between 1953 and 2017. The relative importance of covariates for the evolution of soil structure was identified and their non-linear and non-monotonic effects on the KL divergence were investigated through partial dependence analysis. To reveal any differences between topsoils (0–30 cm; n = 174) and subsoils (30–100 cm; n = 257), the same analysis was repeated separately on these two subsets. The covariates were able to explain on average more than 50% of the variation in KL divergence for all soil samples and when only subsoil samples were included. However, the predictions were poorer for topsoil samples (≈ 35%), underlining the complex dynamics of soil structure in agricultural topsoils. Parent material was the most important predictor for the KL divergence, followed by clay content for all soil samples and sampling year for only subsoil samples. Mean annual air temperature ranked third and annual precipitation ranked fourth for subsoil samples. However, it remains unclear whether the effects of climate factors are direct (e.g., freezing and thawing, wetting and drying, rainfall impact) or indirectly expressed through interactions with soil management. The partial dependence analysis revealed a soil organic carbon threshold of around 3% below which soil structure starts to deteriorate. Besides this, our results suggest that subsoil structure in the agricultural land of Sweden deteriorated steadily during the 1950′s to 1970′s, which we attribute to traffic compaction as a consequence of agricultural intensification. We discuss our findings in the light of data bias, laboratory methods and multicollinearity and conclude that the approach followed here gave valuable insights into the drivers of soil structure evolution in agricultural soils of the temperate-boreal zone. Theses insights will be of use to inform soil management interventions that address soil structure or soil properties and functions related to it.
Forfattere
Aline Fugeray-Scarbel Laurent Bouffier Stéphane Lemarié Leopoldo Sánchez Ricardo Alia Chiara Biselli Joukje Buiteveld Andrea Carra Luigi Cattivelli Arnaud Dowkiw Luis Fontes Agostino Fricano Jean-Marc Gion Jacqueline Grima-Pettenati Andreas Helmersson Francisco Lario Luis Leal Sven Mutke Giuseppe Nervo Torgny Persson Laura Rosso Marinus JM Smulders Arne Steffenrem Lorenzo Vietto Matti HaapanenSammendrag
Genetically improved forest reproductive materials are now widely accessible in many European countries due to decades of continuous breeding efforts. Tree breeding does not only contribute to higher-value end products but allows an increase in the rate of carbon capture and sequestration, helping to mitigate the effects of climate change. The usefulness of breeding programmes depends on (i) the relevance of the set of selected traits and their relative weights (growth, drought tolerance, phenology, etc.); (ii) the explicit management of targeted and “neutral” diversity; (iii) the genetic gain achieved; and (iv) the efficiency of transferring diversity and gain to the plantation. Several biological factors limit both operational breeding and mass reproduction. To fully realise the potential of tree breeding, the introduction of new technologies and concepts is pivotal for overcoming these constraints. We reviewed several European breeding programmes, examining their current status and factors that are likely to influence tree breeding in the coming decades. The synthesis was based on case studies developed for the European Union-funded B4EST project, which focused on eight economically important tree species with breeding histories and intensities ranging from low-input breeding (stone pine, Douglas-fir and ash) to more complex programmes (eucalyptus, maritime pine, Norway spruce, poplar, and Scots pine). Tree breeding for these species is managed in a variety of ways due to differences in species’ biology, breeding objectives, and economic value. Most programmes are managed by governmental institutes with full or partial public support because of the relatively late return on investment. Eucalyptus is the only tree species whose breeding is entirely sponsored and managed by a private company. Several new technologies have emerged for both phenotyping and genotyping. They have the potential to speed up breeding processes and make genetic evaluations more accurate, thereby reducing costs and increasing genetic gains per unit of time. In addition, genotyping has allowed the explicit control of genetic diversity in selected populations with great precision. The continuing advances in tree genomics are expected to revolutionise tree breeding by moving it towards genomic-based selection, a perspective that requires new types of skills that are not always available in the institutions hosting the programmes. We therefore recognise the importance of promoting coordination and collaboration between the many groups involved in breeding. Climate change is expected to bring in new pests and diseases and increase the frequency of extreme weather events such as late frosts and prolonged droughts. Such stresses will cause slow growth and mortality, reducing forest productivity and resilience. Most of these threats are difficult to predict, and the time-consuming nature of conventional breeding does not allow for an adequate and timely reaction. We anticipate that most breeding programmes will need to revise their selection criteria and objectives to place greater emphasis on adaptive performance, tolerance to multiple environmental stresses, stability in different environments, and conservation of genetic diversity. Testing breeding materials in a variety of environments, including potentially contrasting climates, will become increasingly important. Climate change may also force the incorporation of new genetic resources that provide new useful adaptations, which may involve the use of new, previously unexplored gene pools or hybridisation, with the enormous challenge of incorporating useful alleles without adding along an unfavourable genetic background. Decision-support tools to help landowners and foresters select the best-performing forest reproductive material in each specific environment could also help reduce the impact of climate change.
Forfattere
Elise Van Eynde Felipe Yunta Cristina Arias-Navarro Daniele De Rosa Iñigo Virto Panos Panagos Diana Vieira Calogero Schillaci; Alberto Orgiazzi Stefano Salata Philippe Hinsinger Dalila Serpa Frederik Bøe Gerard Ros Eduardo Moreno Jimenez Christopher Poeplau Gabriele Buttafuoco Arwyn Jones Cristiano Ballabio Emanuele Lugato Stefan Frank Tiphaine Chevallier Rosa M. Poch Pasquale Borrelli Francis Matthews Diana Vieira Matthias Vanmaercke Jean Poesen Günay Erpul Velibor Spalevic Snezana Dragovic Yuriy Dmytruk Anita Bernatek-Jakiel Philipp Saggau Leonidas Liakos Christine Alewell Mathieu Lamandé Diego Baragaño Olivier Evrard Tanja Reiff Vera Silva Ana De La Torre Chaosheng Zhang Piort Wojda Chiara Piccini Claudia Cagnarini Zoka Melpomeni Fuat Kaya Kitti Balog Noelia García Franco Simone Scarpa Timo Breure Maria J.I. Briones Julia Köninger Marcel Van Der Heijden Nikolaos Monokrousos Maëva Labouyrie Davorka K. Hackenberger Ottone Scammacca Michele Munafò Silvia Ronchi Andrea ArcidiaconoSammendrag
Det er ikke registrert sammendrag
Forfattere
Wilson Lara Henao Rasmus Astrup Ari Hietala Kobra Maleki Helmer Belbo Clara Antón FernándezSammendrag
1. Root and butt rot caused by pathogenic fungi in the genera Heterobasidion and Armillaria is a pressing issue in managed Norway spruce forests. The disease results in financial losses for the forest owners and reduces the volume of wood that can be used in long-lived products. Pathogenic wood decay fungi spread either with the aid of airborne spores or via mycelial growth among neighbouring trees, the latter leading to clustering (tendency of decayed trees to be in close proximity relative to their neighbouring trees) of decay-affected trees in forests. Understanding the spatial patterns of the decay-affected trees at the forest stand level is vital for designing management strategies to address this problem. 2. We examined decay clustering in 273 clear-cut Norway spruce stands in Norway using harvester-recorded data on spatial occurrence of decayed and healthy Norway spruce trees. We tested clustering using three global-cluster tests that account for population density and distribution, evaluating clustering without identifying specific cluster locations. 3. The proportions of clustered and non-clustered stands differed depending on the statistical test used for clustering assessment, resulting in overall agreement of 32.8% for clustered and 36.9% for non-clustered. Clustered stands exhibited a median cluster distance (maximum distance between the decay-affected trees within a cluster) of 12 m (Inter-Quantile Range, IQR, 6–20 m) and a median of 6 (IQR 3–16) nearest neighbour trees (number of decayed trees forming a cluster), estimates comparable with prior studies focused on assessment of trees infected by mycelial spread of the same fungal individual. The decay incidence in the clustered stands was 16.24%, while the non-clustered stands had a butt-rot incidence of 20.97%. In clustered stands the average number of trees per hectare was higher (693) than in non-clustered stands (553). 4. Synthesis and applications: Our study demonstrates that Norway spruce stands display a diverse range of spatial patterns of butt rotted trees. We found that higher densities of Norway spruce trees probably facilitate the vegetative spread of pathogenic wood decay fungi, leading to clustering of decay-affected trees. To disrupt the spread of decay fungi between tree generations, precision planting of trees other than Norway spruce around infested stumps of prior generation trees has been recommended by earlier studies. We discussed the potential of using harvester-derived geoposition data for butt-rotted trees upon planning and execution of forest regeneration.