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Health and economic assessment of ultrafine particles in Stockholm : Impacts of electrification and local policies
No full textLack of robustness of hydrological models : a large-sample diagnosis and an attempt to identify hydrological and climatic drivers
No full textReliable environmental DNA detection of planktonic biodiversity : Minimum sample volume for DNA metabarcoding
No full textEnvironmental DNA (eDNA)-based detection has become an attractive method for determining biodiversity as it can provide more detailed information compared to traditional morphology-based approaches. This is especially relevant for targeting overall biodiversity or screening for the presence of harmful algal bloom (HAB) species. However, despite the availability of several general guidelines, the workflow for marine environments has yet to be standardised. This lack of standardisation complicates the comparison between samples across different monitoring programmes and projects. This project focused on the first step of the workflow – determining and standardising the minimum reliable sample volume needed to detect phytoplankton diversity under various environmental and biological conditions. A study and a workshop were conducted to test different sample volumes (1000 mL, 500 mL, 200 mL, and 20 mL), using samples collected from the Baltic and North Seas and northwestern Atlantic Ocean under various environmental conditions. Across the studied samples, 200 mL was identified as a sufficient sample volume to detect various species across the different volumes tested. This result represents an important first step towards standardising the eDNA-based approach and incorporating it into routine monitoring. Furthermore, the results of this project are expected to contribute to reducing the time and resources required for monitoring
Impacts of hypoxia on boreal lake biogeochemistry and productivity : a 4-year whole-ecosystem BACI experiment
No full textDrivers of high-frequency extreme sea levels around northern Europe - synergies between recurrent neural networks and random forest
No full textEvaluation of Modeled Carbon Monoxide and Methane Columns in the High Arctic Using TCCON Measurements
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