Publications of the NFI
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Clerc‐Schwarzenbach F., Astagneau P.C., Muñoz Castro E., van Meerveld I., Seibert J., Andréassian V. (2026) Cheeky cheating or a sensible strategy? 'Sweep parameters' in bucket‐type hydrological models. Hydrol. Process. 40(1), e70375 (7 pp.). https://doi.org/10.1002/hyp.70375
The model performance of bucket-type hydrological models is often improved by including an additional path for water to enter or leave the catchment, aside from precipitation, evaporation, and streamflow. We refer to parameters allowing for such an additional path as 'sweep parameters'. Far from being an exception, sweep parameters are rather ubiquitous. In this commentary, we discuss the relevance and justifiability of sweep parameters. We argue that although the use of sweep parameters can be considered cheating, as it is a way to fix the water balance, it is a transparent way to do so. Furthermore, in some cases they may represent actual processes. We also present some results on the effects of a sweep parameter on the performance and robustness of two bucket-type hydrological models. We find that sweep parameters do not necessarily reduce model robustness towards variations in the meteorological inputs and often improve streamflow simulations. Therefore, sweep parameters should not per se be frowned upon, as long as they are clearly described and not hidden under the rug.
DOI: 10.1002/hyp.70375
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Huo J., Stadelmann G., Burg V., Subal L., Jakobs A., Thürig E., Hellweg S. (2026) Prospective climate change impacts of Swiss forest management and wood utilization strategies by integrating biogenic carbon dynamics. Resour. Conserv. Recycl. 226, 108692 (12 pp.). https://doi.org/10.1016/j.resconrec.2025.108692
Forests and wood products play crucial roles in climate change mitigation, yet their climate impacts remain poorly understood. We couple empirical Swiss forest development models with dynamic life cycle assessment to evaluate climate impacts of two forest management scenarios (reference and increased harvest) and four wood utilization scenarios (business-as-usual, increased material use, extended lifetime, and chemical substitution) in Switzerland from 2014 to 2113. Results reveal that increased harvest leads to higher climate impacts compared to the reference management practices under empirical modeling, contradicting simplified regrowth model conclusions favoring increased harvest. The contrasting results underscore uncertainty in forest carbon projections, warning against simplified carbon-neutrality assumptions of biogenic CO2 emissions. Increased wood use for construction applications and extended product lifetimes demonstrate climate benefits, while diverting wood from energy to chemical production increases emissions. We emphasize the necessity of improved forest carbon modeling for informed climate mitigation strategies and recommend prioritizing long-lived wood construction applications.
DOI: 10.1016/j.resconrec.2025.108692
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Li B., Pang Y., Kükenbrink D., Wang L., Kong D., Marty M. (2026) ITS-Net: a platform and sensor agnostic 3D deep learning model for individual tree segmentation using aerial LiDAR data. ISPRS J. Photogramm. Remote Sens. 231, 719-744. https://doi.org/10.1016/j.isprsjprs.2025.11.019
Recent advances in aerial Light Detection and Ranging (LiDAR) technologies have revolutionized the capability to characterize individual tree structure, enabling detailed ecological analyses at the tree level. A critical prerequisite for such analysis is an accurate individual tree segmentation. However, this task remains challenging due to the complexity of forest environments and varying quality of point clouds collected by diverse aerial sensors and platforms. Existing methods are mostly designed for a single aerial platform or sensor and struggle with complex forest environments. To address these limitations, we propose ITS-Net, an aerial platform and sensor-agnostic deep learning model for individual tree segmentation, which integrates three modules designed to enhance its learning capability under complex forest environments. To facilitate and evaluate its platform and sensor-agnostic capabilities, we constructed AerialTrees, a comprehensive individual tree segmentation dataset that included aerial LiDAR data collected with point densities ranging from 50 to 10,000 pts/m2 using different sensors from ALS and ULS platforms over four climate zones. This dataset also included 2,903 individual trees that had been labeled manually. ITS-Net outperformed state-of-the-art individual tree segmentation methods on AerialTrees, achieving the highest average performance with a detection rate of 94.8 % and an F1-score of 90.9 %. It achieved an F1-score of 88.1 % when tested on the publicly available FOR-instance dataset. ITS-Net also performed better than the state-of-the-art ForAINet method for multi-layered canopy segmentation, outperforming the latter by 12.3 % in detecting understory vegetation. When directly transferred to the five study sites of the FOR-instance dataset as well as the study sites in Switzerland and Russia, ITS-Net produced accuracies that were reasonably close to those produced by several other algorithms trained over those study sites. These results were achieved without requiring efforts to address differences in LiDAR data characteristics through explicit data preprocessing or to fine tune the parameters of the deep learning model, demonstrating ITS-Net's robustness for segmenting various aerial LiDAR point clouds acquired using different sensors from different aerial platforms. As a sensor and platform agnostic method, ITS-Net may provide an end-to-end solution needed to facilitate the use of rapidly evolving aerial LiDAR technology in various forestry applications. The AerialTrees dataset developed through this study is a significant contribution to the very few publicly available labeled LiDAR datasets that are crucial for calibrating, testing, and benchmarking individual tree segmentation algorithms. Our code and data are available at: Global warming has shifted the timing of leaf senescence, influencing water and carbon cycles in terrestrial ecosystems. Climate conditions preceding leaf senescence play a critical role in regulating senescence timing, yet the temporal variation in the effect of temperature on leaf senescence remain unclear, hindering accurate predictions of growing season length. Based on 321,639 in situ phenological records of four dominant European tree species (Aesculus hippocastanum, Betula pendula, Fagus sylvatica, and Quercus robur) collected from 1950 to 2021, we found that leaf senescence has significantly delayed by 5.7 days over the past seven decades, primarily driven by preseason temperature and the timing of spring leaf-out. Rising preseason temperatures delayed leaf senescence (β = 0.37, P < 0.05), whereas earlier leaf-out timing advanced it (β = 0.32, P < 0.05). More importantly, the effects of temperature on leaf senescence have shifted significantly, with the delaying effect of temperature becoming stronger, especially in cold regions. This variation could be explained by the divergent effects of early- and late-season temperature on leaf senescence, as well as by the shortened optimal preseason length of temperature (−2.3 days per decade). Our study highlights the importance of the optimal preseason length of temperature in regulating leaf senescence and emphasizes the need to incorporate its variation into senescence models to improve predictions of growing season length and carbon-cycle dynamics..
DOI: 10.1016/j.isprsjprs.2025.11.019
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Trummer J., Wunderli J.M., Schäffer B., Hunziker M., Tobias S., Heusser A., … Hegetschweiler T. (2026) The role of visual and acoustical characteristics on forest attractiveness. Urban For. Urban Green. 118, 129306 (15 pp.). https://doi.org/10.1016/j.ufug.2026.129306
Recreational forests play a vital role for human well-being and recreation. Yet, the role of and interplay between visual and auditory environmental characteristics in forest recreation remain underexplored. This study investigates how multisensory characteristics, particularly visual forest characteristics and the local soundscape, influence perceived forest attractiveness, perceived restfulness, and visit frequency aiming to gain a holistic understanding of forest visitors' multisensory perceptions of recreational environments. Employing a mixed-method approach, we conducted quantitative surveys with a total of 482 participants and recordings of the local soundscape at 20 study sites across Switzerland's lowlands with high recreational demand, which represent Swiss National Forest Inventory sample plots. Multilevel regression models combining physical forest data, acoustic, psychoacoustic and sound categories (e.g., birdsong, road traffic etc.) obtained from recordings, and survey data revealed that personal characteristics and individual soundscape perceptions accounted for the majority of variance for the three investigated variables. Notably, natural auditory stimuli such as birdsong enhanced perceived visual attractiveness, while anthropogenic sounds (e.g., helicopters, road traffic) significantly diminished restfulness and reduced visit frequency. Ground vegetation features, such as moss and ferns, also positively influenced perceptions, while dense understory and deadwood had negative impacts. The results highlight the importance of subjective, multisensory experience (e.g., perceived soundscape quality) over environmental characteristics and external sounds in shaping forest preferences. The study’s findings further emphasize the importance of integrating soundscape considerations into forest planning to maintain and enhance restorative qualities, as well as the need for holistic, multisensory strategies in recreational forest management.
DOI: 10.1016/j.ufug.2026.129306
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Wunderlich A.C., Hunziker M., Hegetschweiler K.T., Bauer N., Palm T., Weinbrenner H., … Salak B. (2026) Exploring forest visits: comparing experiences across Switzerland, Baden-Württemberg, and Bayern in Germany. Urban For. Urban Green. 117, 129228 (24 pp.). https://doi.org/10.1016/j.ufug.2025.129228
Urban and peri-urban forests play an increasingly important role in public health and recreation, particularly in the context of urbanization and demographic change. This study compares forest visit patterns across Switzerland, Baden-Württemberg, and Bavaria based on harmonized, large-scale survey data. We analyze visit frequency, motives, satisfaction, and perceived forest health through multilevel and Bayesian models. Results show that individual factors strongly shape satisfaction and visit frequency, while regional effects are minimal. Our findings highlight the need for user-centered forest management that considers diverse motives and especially the needs of younger and more frequent users in urbanizing contexts.
DOI: 10.1016/j.ufug.2025.129228