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
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.
Forfattere
Kristian Hansen Håvard Steinshamn Matthias Koesling Tommy Dalgaard Bjørn Gunnar Hansen Sissel HansenSammendrag
Dairy farming yields milk and meat; however, production is linked with an environmental burden (Wattiaux et al., 2019). In our study N-intensity, GHG emission and land use occupation at 200 dairy farms from central Norway was calculated from cradle to farm gate. Nitrogen intensity was calculated as sum of N from purchased inputs, biological N-fixation, atmospheric N-deposition, N-surplus from off-farm production of ingredients for concentrates and roughage and of bought animals divided by N in delivered milk and meat (Koesling et al., 2017). The organic farms (n=15) had a lower N-intensity than conventional managed farms (n=185) (5.0 vs 6.9 kg N/kg N). Mainly explained by lower use of imported N in the organic farm group. The organic managed farms, however, had a higher land use occupation than conventional farms (3.6 vs 2.9 m2 per 2.78 MJ edible energy in milk or meat delivered (2.78 MJMM)). The GHG emissions per 2.78 MJ edible energy in milk or meat was on average 1.4 kg CO2/2.78 MJMM edible energy for all farms (n=200). The GHG emission was correlated with N-intensity (r2=0.85), which indicate that reduced N-intensity is associated with lower GHG emissions per product unit. Our results support that improved utilization of local resources, e.g. manure, legumes in grass- based forage are likely to reduce N-intensity at both organic and conventional managed farms. Reduced N-intensity will likely lessen GHG emissions. The reduced N-intensity and GHG emission came at an expense of increased land use occupation per produced product. References Koesling, M., Hansen, S., Bleken, M.A., 2017. Variations in nitrogen utilisation on conventional and organic dairy farms in Norway. Agric Syst. 157, 11–21. https://doi.org/10.1016/j.agsy.2017.06.001. Wattiaux, M.A., Uddin, M.E., Letelier, P., Jackson, R.D., Larson, R.A., 2019. INVITED REVIEW: Emission and mitigation of greenhouse gases from dairy farms: The cow, the manure, and the field. AAS. 35 (2), 238-254. https://doi.org/10.15232/aas.2018-01803.
Sammendrag
Ensiling of whole-crop biomass of barley before full maturity is common practice in regions with a short growing season. The developmental stage of barley at harvest can have a large impact on yield and nutritive composition. The relationships between crop growth, environmental conditions and crop management can be described in process-based simulation models. Some models, including the Basic Grassland (BASGRA) model, have been developed to simulate the yield and nutritive value of forage grasses, and usually evaluated against metrics of relevance for whole-crop silage. The objectives of this study were to: i) modify the BASGRA model to simulate whole-crop spring barley; ii) evaluate the performance of this model against empirical data on dry matter (DM) yield and nutritive value attributes from field experiments, divided into geographical regions; and iii) evaluate DM yield, nutritive value and cutting date under current and future climate conditions for three locations in Sweden and four cutting regimes. Main model modifications included addition of a spike pool, equations for carbon (C) and nitrogen (N) allocation to the spike pool and equations for C and N translocation from vegetative plant parts to spikes. Model calibration and validation against field trial data from Sweden, including samples harvested from late anthesis stage to hard dough stage that were either pooled or divided into regions, showed better prediction accuracy, evaluated as normalised root mean squared error (RMSE), of neutral detergent fibre (NDF) (7.58–18.4%) than of DM yield (16.8–27.8%), crude protein (15.5–23.2%) or digestible organic matter in the DM (DOMD) (12.0–22.2%). Model prediction using weather data representing 1990–2020 and 2021–2040 climate conditions for three locations in Sweden (Skara, Umeå, Uppsala) showed lower DM yield, earlier harvest and slightly higher NDF concentration on average (across locations and developmental stage at cutting) when using near-future climate data rather than historical data. The model can be used to evaluate whole-crop barley performance under production conditions in Sweden or in other countries with similar climate, soils and crop management regimes.
Sammendrag
Winter storage of seedlings in freezers reduces the amount of heat sum available for growth in the following growing season compared to seedlings stored outdoors. To test the effects of a reduced growing period on the autumn frost hardiness of the six species most used in Icelandic afforestation, seedlings were stored outdoors or in a freezer during winter. In spring, the seedlings were planted on 24 May, 7 June, 21 June, and 5 July, and the frost hardiness of all treatments was tested on 12 and 26 September. In general, the probability of freezing damage increased with a later planting date, with outdoor-stored seedlings having the lowest probability of damage. The timing of frost events was of great importance; the later the freezing date, the less damage was observed. Growth cessation occurred at different times for each species, and they responded differently to the reduced heat sum. Lodgepole pine and birch accumulated the most frost hardiness in September. Sitka spruce had less autumn frost hardiness than Lutz spruce. Hybrid larch accumulated less frost hardiness than Russian larch and was most sensitive to the reduced heat sum. The results can be used to determine which species should be prioritised in frozen storage with regard to Iceland‘s short growing season.
Forfattere
Nga Nguyen Ulrich Bergmann Laura Elina Jaakola Hely Häggman Soile Jokipii-Lukkari Katalin TothSammendrag
Bilberry (Vaccinium myrtillus L.) is a wild berry species that is prevalent in northern Europe. It is renowned and well-documented for its nutritional and bioactive properties, especially due to its anthocyanin content. However, an overview of biological systems governing changes in other crucial quality traits, such as size, firmness, and flavours, has received less attention. In the present study, we investigated detailed metabolomic and proteomic profiles at four different ripening stages of bilberry to provide a comprehensive understanding of overall quality during fruit ripening. By integrating omics datasets, we revealed a novel global regulatory network of plant hormones and physiological processes occurring during bilberry ripening. Key physiological processes, such as energy and primary metabolism, strongly correlate with elevated levels of gibberellic acids, jasmonic acid, and salicylic acid in unripe fruits. In contrast, as the fruit ripened, processes including flavour formation, cell wall modification, seed storage, and secondary metabolism became more prominent, and these were associated with increased abscisic acid levels. An indication of the increase in ethylene biosynthesis was detected during bilberry development, raising questions about the classification of non-climacteric and climacteric fruits. Our findings extend the current knowledge on the physiological and biochemical processes occurring during fruit ripening, which can serve as a baseline for studies on both wild and commercially grown berry species. Furthermore, our data may facilitate the optimization of storage conditions and breeding programs, as well as the future exploration of beneficial compounds in berries for new applications in food, cosmetics, and medicines.
Forfattere
Markus A. K. Sydenham Yoko Dupont Anders Nielsen Jens Olesen Henning Bang Madsen Astrid Brekke Skrindo Claus Rasmussen Megan Sara Nowell Zander Venter Stein Joar Hegland Anders Gunnar Helle Daniel Ingvar Jeuderan Skoog Marianne Strand Torvanger Kaj-Andreas Hanevik Sven Emil Hinderaker Thorstein Paulsen Katrine Eldegard Trond Reitan Graciela Monica RuschSammendrag
Climate change, landscape homogenization and the decline of beneficial insects threaten pollination services to wild plants and crops. Understanding how pollination potential (i.e. the capacity of ecosystems to support pollination of plants) is affected by climate change and landscape homogenization is fundamental for our ability to predict how such anthropogenic stressors affect plant biodiversity. Models of pollinator potential are improved when based on pairwise plant-pollinator interactions and pollinator´s plant preferences. However, whether the sum of predicted pairwise interactions with a plant within a habitat (a proxy for pollination potential) relates to pollen deposition on flowering plants has not yet been investigated. We sampled plant-bee interactions in 68 Scandinavian plant communities in landscapes of varying land-cover heterogeneity along a latitudinal temperature gradient of 4–8 C°, and estimated pollen deposition as the number of pollen grains on flowers of the bee-pollinated plants Lotus corniculatus, and Vicia cracca. We show that plant-bee interactions, and the pollination potential for these bee-pollinated plants increase with landscape diversity, annual mean temperature, plant abundance, and decrease with distances to sand-dominated soils. Furthermore, the pollen deposition in flowers increased with the predicted pollination potential, which was driven by landscape diversity and plant abundance. Our study illustrates that the pollination potential, and thus pollen deposition, for wild plants can be mapped based on spatial models of plant-bee interactions that incorporate pollinator-specific plant preferences. Maps of pollination potential can be used to guide conservation and restoration planning.