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.
2022
Authors
Laura D. Ngau Sim S. Fong Kho L. Khoon Elisa Rumpang Harri Vasander Jyrki Jauhiainen Kim Yrjälä Hanna Marika SilvennoinenAbstract
Water table conditions in drained peatlands affect peat decomposition, fluvial carbon and greenhouse gas emissions, and plant growth in oil palm plantations. This study illustrates the spatial heterogeneity of soil moisture profiles in cultivated tropical peat under oil palm plantation and uncultivated secondary forest, using maps. At a study plot under each land use the geographical coordinates of sampling points, tree locations and other features were recorded. Peat soil samples were taken at depths of 0–50 cm, 50–100 cm, 100–150 cm and 150–200 cm, and their moisture contents were determined. Overall, soil moisture content was higher in secondary forest than in oil palm plantation due to land management activities such as drainage and peat compaction in the latter. Significant differences were observed between the topsoil (0–50 cm) and deeper soil layers under both land uses. Soil moisture maps of the study plots interpolated using geographical information system (GIS) software were used to visualise the spatial distributions of moisture content in soil layers at different depths (0–50 cm, 50–100 cm, 100–150 cm, 150–200 cm). Moisture content in the 0–50 cm soil layer appeared to be inversely related to elevation, but the correlation was not statistically significant. On the other hand, there was a significant positive correlation between soil moisture content and the diameters of oil palm trunks. Palm trees with negative growth of trunk diameter were mostly located in subplots which were relatively dry and/or located near drains. The results of this study indicate that soil moisture mapping using GIS could be a useful tool in improving the management of peatland to promote oil palm growth.
Authors
Saheba Bhatnagar Stefano Puliti Bruce Talbot Joachim Bernd Heppelmann Johannes Breidenbach Rasmus AstrupAbstract
Wheel ruts, i.e. soil deformations caused by harvesting machines, are considered a negative environmental impact of forest operations and should be avoided or ameliorated. However, the mapping of wheel ruts that would be required to monitor harvesting operations and to plan amelioration measures is a tedious and time-consuming task. Here, we examined whether a combination of drone imagery and algorithms from the field of artificial intelligence can automate the mapping of wheel ruts. We used a deep-learning image-segmentation method (ResNet50 + UNet architecture) that was trained on drone imagery acquired shortly after harvests in Norway, where more than 160 km of wheel ruts were manually digitized. The cross-validation of the model based on 20 harvested sites resulted in F1 scores of 0.69–0.84 with an average of 0.77, and in total, 79 per cent of wheel ruts were correctly detected. The highest accuracy was obtained for severe wheel ruts (average user’s accuracy (UA) = 76 per cent), and the lowest accuracy was obtained for light wheel ruts (average UA = 67 per cent). Considering the nowadays ubiquitous availability of drones, the approach presented in our study has the potential to greatly increase the ability to effectively map and monitor the environmental impact of final felling operations with respect to wheel ruts. The automated mapping of wheel ruts may serve as an important input to soil impact analyses and thereby support measures to restore soil damages.
Authors
Camilla Risvoll Diego Galafassi Siri Veland Mats Pavall Tom Lifjell Aase-Kristine Aasen Lundberg Svein EilertsenAbstract
The categories and concepts in the existing official land-use maps have been under improvements over recent years; however, this study from Nordland, northern Norway, shows that they continue to pose several dilemmas when aiming to better capture the impacts of multiple land uses on reindeer herding. While these developments have done much to better communicate the presence of reindeer herding to developers and planners, there remain significant challenges to achieve best practices. In particular, the confluence of multiple landscape features, for instance, roads, farmland, ecoregions, tenure, pastures, tourism paths and cabins, may have interactions that create cumulative impacts that do not “add up” neatly across map layers. Migration routes, herding routes, and resting areas have been introduced in these maps. In collaboration with reindeer herders, this article analyses how to enrich mapping practices by for example including bottlenecks, parallel to increased attention to influence zones and avoidance zones, as important emergent impacts of multiple interacting features of the landscape. Our research reveals how local knowledge developed by herders through their “presence in the landscape” is better capable of accounting for interactions and cumulative dimensions of landscape features. Through our participatory mapping approach with Sámi reindeer herders, we focus on ways of combining reindeer herders’ knowledge and GIS maps and demonstrate the potential in collaborative work between herders and policymakers in generating a richer understanding of land-use change. We conclude that the practical knowledge of people inhabiting and living with the landscape and its changing character generates a rich understanding of cumulative impacts and can be harnessed for improved land-use mapping and multi-level governance.
Authors
Anna Birgitte MilfordAbstract
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Authors
Katrin ZimmerAbstract
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Authors
Giorgia CarnovaleAbstract
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Authors
Giorgia Carnovale Carmen Lama Sonia Torres Filipa Rosa Lalia Mantecon Svein Jarle Horn Kari Skjånes Carlos InfanteAbstract
Tetraselmis chui is known to accumulate starch when subjected to stress. This phenomenon is widely studied for the purpose of industrial production and process development. Yet, knowledge about the metabolic pathways involved is still immature. Hence, in this study, transcription of 27 starch-related genes was monitored under nitrogen deprivation and resupply in 25 L tubular photobioreactors. T. chui proved to be an efficient starch producer under nitrogen deprivation, accumulating starch up to 56% of relative biomass content. The prolonged absence of nitrogen led to an overall down-regulation of the tested genes, in most instances maintained even after nitrogen replenishment when starch was actively degraded. These gene expression patterns suggest post-transcriptional regulatory mechanisms play a key role in T. chui under nutrient stress. Finally, the high productivity combined with an efficient recovery after nitrogen restitution makes this species a suitable candidate for industrial production of high-starch biomass.
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