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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

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Sammendrag

1. Wild pollinators are crucial for ecosystem functioning and human food production and often rely on floral resources provided by different (semi-) natural ecosystems for survival. Yet, the role of European forests, and especially the European forest herb layer, as a potential provider of floral resources for pollinators has scarcely been quantified. 2. In this study, we measured the potential nectar production (PNP) of the forest herb layer using resurvey data across 3326 plots in temperate forests in Europe, with an average time interval of 41 years between both surveys in order to assess (i) the importance of the forest herb layer in providing nectar for wild pollinators, (ii) the intra-annual variation of PNP, (iii) the overall change in PNP between survey periods and (iv) the change in intra-annual variation of PNP between survey periods. The PNP estimates nectar availability based on the relative cover of different plant species in the forest herb layer. Although PNP overestimates actual nectar production, relative differences amongst plots provide a valid and informative way to analyse differences across time and space. 3. Our results show that the forest herb layer has a large potential for providing nectar for wild pollinator communities, which is greatest in spring, with an average PNP of almost 16 g sugar/m2/year. However, this potential has drastically declined (mean plot-level decline >24%). 4. Change in light availability, associated with shifts in canopy structure and canopy composition, is the key driver of temporal PNP changes. 5. Synthesis. Our study shows that if management activities are carefully planned to sustain nectar-producing plant species for wild pollinators, European forest herb layers and European forests as a whole can play key roles in sustaining wild pollinator populations.

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Sammendrag

Biological nitrogen fixation is a fundamental part of ecosystem functioning. Anthropogenic nitrogen deposition and climate change may, however, limit the competitive advantage of nitrogen-fixing plants, leading to reduced relative diversity of nitrogen-fixing plants. Yet, assessments of changes of nitrogen-fixing plant long-term community diversity are rare. Here, we examine temporal trends in the diversity of nitrogen-fixing plants and their relationships with anthropogenic nitrogen deposition while accounting for changes in temperature and aridity. We used forest-floor vegetation resurveys of temperate forests in Europe and the United States spanning multiple decades. Nitrogen-fixer richness declined as nitrogen deposition increased over time but did not respond to changes in climate. Phylogenetic diversity also declined, as distinct lineages of N-fixers were lost between surveys, but the “winners” and “losers” among nitrogen-fixing lineages varied among study sites, suggesting that losses are context dependent. Anthropogenic nitrogen deposition reduces nitrogen-fixing plant diversity in ways that may strongly affect natural nitrogen fixation.

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Sammendrag

Detailed forest inventories are critical for sustainable and flexible management of forest resources, to conserve various ecosystem services. Modern airborne laser scanners deliver high-density point clouds with great potential for fine-scale forest inventory and analysis, but automatically partitioning those point clouds into meaningful entities like individual trees or tree components remains a challenge. The present study aims to fill this gap and introduces a deep learning framework, termed ForAINet, that is able to perform such a segmentation across diverse forest types and geographic regions. From the segmented data, we then derive relevant biophysical parameters of individual trees as well as stands. The system has been tested on FOR-Instance, a dataset of point clouds that have been acquired in five different countries using surveying drones. The segmentation back-end achieves over 85% F-score for individual trees, respectively over 73% mean IoU across five semantic categories: ground, low vegetation, stems, live branches and dead branches. Building on the segmentation results our pipeline then densely calculates biophysical features of each individual tree (height, crown diameter, crown volume, DBH, and location) and properties per stand (digital terrain model and stand density). Especially crown-related features are in most cases retrieved with high accuracy, whereas the estimates for DBH and location are less reliable, due to the airborne scanning setup.