Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2025
Abstract
Accurately predicting whether pedestrians will cross in front of an autonomous vehicle is essential for ensuring safe and comfortable maneuvers. However, developing models for this task remains challenging due to the limited availability of diverse datasets containing both crossing (C) and non-crossing (NC) scenarios. Therefore, we propose a procedure that leverages synthetic videos with C/NC labels and an untrained model whose architecture is designed for C/NC prediction to automatically produce C/NC labels for a set of real-world videos. Thus, this procedure performs a synth-to-real unsupervised domain adaptation for C/NC prediction, so we term it S2R-UDA-CP. To assess the effectiveness of S2R-UDA-CP in self-labeling, we utilize two state-of-the-art models, PedGNN and ST-CrossingPose, and we rely on the publicly-available PedSynth dataset, which consists of synthetic videos with C/NC labels. Notably, once the real-world videos are self-labeled, they can be used to train models different from those used in S2R-UDA-CP. These models are designed to operate onboard a vehicle, whereas S2R-UDA-CP is an offline procedure. To evaluate the quality of the C/NC labels generated by S2R-UDA-CP, we also employ PedGraph+ (another literature referent) as it is not used in S2R-UDA-CP. Overall, the results show that training models to predict C/NC using videos labeled by S2R-UDA-CP achieves performance even better than models trained on human-labeled data. Our study also highlights different discrepancies between automatic and human labeling. To the best of our knowledge, this is the first study to evaluate synth-to-real self-labeling for C/NC prediction.
Authors
Daniel Moreno-Fernández Johannes Breidenbach Isabel Cañellas Gherardo Chirici Giovanni D’amico Marco Ferretti Francesca Giannetti Stefano Puliti Sebastian Schnell Ross Shackleton Mitja Skudnik Iciar AlberdiAbstract
Forest biodiversity is a multifaceted term encompassing tree and shrub diversity and the diversity of other life forms such as animals or fungi. Extensive forest monitoring networks such as National Forest Inventories or the International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forest plots have implemented biodiversity-monitoring protocols to satisfy increasing information demands. However, these protocols often evaluate biodiversity through potential biodiversity indicators (e.g., stand structure and deadwood), which may not provide sufficient information on other aspects of the current forest biodiversity status. In this study, we present the forest biodiversity monitoring results and lessons from a cross-country study to support large-scale monitoring systems. We developed, evaluated, and discussed harmonized protocols, mainly focused on birds and mammals, which extend beyond the traditional features captured in large-scale forest inventories. We leverage information from 30 intensively monitored plots established in six European countries to achieve these goals. The protocols were helpful in recording data that could be used to reproduce biodiversity-related attributes such as measures of forest structure, regeneration, deadwood features, and bird and mammal diversity. Specifically, field data on trees was used to describe structural features of forests such as stand composition and forest complexity. In contrast, composition and regeneration data provided helpful information for other biodiversity indicators. Data gathering to monitor bird and mammal diversity requires revisiting the plots, which involves greater economic investment and human effort. Once the bird and mammal data have been collected, advanced algorithms could facilitate and enhance the efficiency of the analyses. To optimize the monitoring efficiency, we recommend including these two new biodiversity assessments in a subset of extensive survey plots. Furthermore, using standard guidelines for these new assessments across all countries would facilitate the comparison and reporting of statistical data.
Authors
Shaohui Zhang Poul Erik Lærke Mathias Neumann Andersen Junxiang Peng Esben Øster Mortensen Johannes Wilhelmus Maria Pullens Sheng Wang Klaus Steenberg Larsen Davide Cammarano Uffe Jørgensen Kiril ManevskiAbstract
No abstract has been registered
Abstract
Environmental observation networks, such as AmeriFlux, are foundational for monitoring ecosystem response to climate change, management practices, and natural disturbances; however, their effectiveness depends on their representativeness for the regions or continents. We proposed an empirical, time series approach to quantify the similarity of ecosystem fluxes across AmeriFlux sites. We extracted the diel and seasonal characteristics (i.e., amplitudes, phases) from carbon dioxide, water vapor, energy, and momentum fluxes, which reflect the effects of climate, plant phenology, and ecophysiology on the observations, and explored the potential aggregations of AmeriFlux sites through hierarchical clustering. While net radiation and temperature showed latitudinal clustering as expected, flux variables revealed a more uneven clustering with many small (number of sites < 5), unique groups and a few large (> 100) to intermediate (15–70) groups, highlighting the significant ecological regulations of ecosystem fluxes. Many identified unique groups were from under-sampled ecoregions and biome types of the International Geosphere-Biosphere Programme (IGBP), with distinct flux dynamics compared to the rest of the network. At the finer spatial scale, local topography, disturbance, management, edaphic, and hydrological regimes further enlarge the difference in flux dynamics within the groups. Nonetheless, our clustering approach is a data-driven method to interpret the AmeriFlux network, informing future cross-site syntheses, upscaling, and model-data benchmarking research. Finally, we highlighted the unique and underrepresented sites in the AmeriFlux network, which were found mainly in Hawaii and Latin America, mountains, and at under- sampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups.
Authors
Katharina HobrakAbstract
No abstract has been registered
Authors
Arne Verstraeten Andreas Schmitz Bernd Ahrends Nicholas Clarke Wim de Vries Karin Hansen Char Hilgers Carmen Iacoban Tamara Jakovljevic Per Erik Karlsson Till Kirchner Aldo Marchetto Henning Meesenburg Gunilla Pihl Karlsson Anne-Katrin Prescher Anne Thimonier Peter WaldnerAbstract
No abstract has been registered
Authors
Aline Roma Tomaz William Ramos da Silva Thiago Inagaki Emylaine Oliveira Santos Giselle Gomes Monteiro Fracetto Felipe José Cury Fracetto Vitor da Silveira Freitas Diego Victor Babos Débora Milori Abelardo Antônio de Assunção Montenegro Ademir De Oliveira FerreiraAbstract
Knowledge gaps persist regarding mulch decomposition, nutrient dynamics, and microbial responses in semi-arid soils under reclaimed water irrigation. This is a critical issue for water-scarce regions like the Brazilian semi-arid. This study evaluated these processes in cactus-sorghum intercropping systems with mulch under irrigation depths with reclaimed water. The study employed a randomized block design with four replicates, testing irrigation depths of 0 %, 80 %, 100 %, and 120 % of sorghum ETc. Mulch decomposition was monitored for 165 days using litter bags, with subsequent C/N analysis of residual biomass. Soils at 0–0.10 m and 0.10–0.20 m depths were sampled to determine the contents of NO₃−, NH₄+, P, and microbial biomass C (MB-C), basal soil respiration, and aromatization index (ALIFS). Decomposition revealed the highest rates at 10 days (16 %) under 80 % ETc and at 25 days (24 %, 22 %, and 21 %) under 80 %, 100 %, and 120 % ETc, surpassing non-irrigated soils. Residue half-life was 182–196 days. Mulch N content declined most sharply at 10 days (1.2–1.8 g kg−1 in irrigated treatments). Soil NH₄+ and NO₃− peaked in the 0–0.10 m layer, but nitrate decreased by 15–62 % at 65 days, signaling microbial disruption from water excess. MB-C dropped >90 % at 65 days but recovered by 165 days, with the 80 % and 100 % treatments showing the highest MB-C in surface soils. These treatments also increased available P₂O₅ by 46–216 mg kg−1 versus 0 % and 120 % ETc. The ALIFS was higher in irrigated soils, especially at 120 % ETc (0–0.10 m). Reclaimed water irrigation enhanced nutrient supply, decomposition, and microbial activity, reducing synthetic fertilizer dependency while improving soil health in semi-arid agroecosystems.
Abstract
No abstract has been registered
Authors
Holger LangeAbstract
No abstract has been registered
Authors
Niklas Lönnell Kristian Hassel Irina Goldberg Sanna Huttunen Ágúst H. Bjarnason Hans Blom Tomas Hallingbäck Lars Hedenäs Torbjørn Høitomt Kati Pihlaja Tommy Prestø Kimmo Syrjänen Lars Söderström Tauno Ulvinen Henrik WeibullAbstract
We present an updated checklist for all bryophyte species known to occur in the Nordic countries and list occurrences for each taxon from Iceland, the Faroe Islands, Denmark, Svalbard, Jan Mayen, Norway (mainland), Sweden and Finland. Altogether 1276 bryophyte species are included for the region. The checklist includes vernacular names in Icelandic, Danish, Norwegian, Swedish and Finnish. The following new nomenclatural combinations are proposed: Scapania scandica var. parvifolia comb. nov., Andreaea alpina var. hartmanii comb. nov., Didymodon islandicus comb. nov., Ephemerum serratum var. stoloniferum comb. nov., Hygroamblystegium varium var. fluviatile comb. nov., Hygroamblystegium varium var. tenax comb. nov., Ptychostomum arcticum var. purpurascens comb. nov., Ptychostomum intermedium var. nitidulum comb. nov. and Ptychostomum warneum var. mamillatum comb. nov.