Ecosystem ecologist with a focus on belowground plant ecology in tundra and peatlands.
I am an ecosystem ecologist with a passion for high latitude ecosystems and interested in the interplay of plants and their environment. My work in arctic tundra and peatlands focuses on belowground plant processes, such as root phenology and root production, and often includes measurements outside the summer season.
Some of my current projects are outlined below.
Boreal ecosystems are shaped by two major, interacting global change factors: changes in the thickness of the snow cover in winter, and grazing by large herbivores (reindeer). The EcoClimate Experiment at the Oulanka Research Station is a large, long-term experiment which includes snow addition and removal, as well as herbivore exclosures in two habitats: a dry oligotrophic Scots pine forest and a nutrient rich fen site. My goal in this project is to study how reindeer grazing and changes in snow cover influence root dynamics and I will provide non-destructive monitoring data on root dynamics (production, phenology, mortality, turnover) to be linked with other biogeochemical processes at the site. Read more.
The EcoClimate experiment owned and maintained by the Oulanka Research Station (University of Oulu) under the leadership of Riku Paavola, and I additionally collaborate with Maria Väisänen (University of Oulu).
DIG-IT! Digitalisation of Natural Complexity to Solve Socially Relevant Ecological Problems
The most important tool for observing belowground plant activity in the field are so-called minirhizotrons, transparent tubes buried in the soil and a camera to take pictures of roots over time. However, until now the amount of data that could be collected was severely constrained by the extremely time-consuming manual analysis of the resulting images. A single image from complex field settings could easily take a full day to digitize. This means that the biggest obstacle for providing data on root dynamics in high temporal and spatial resolution is the digitization of minirhizotron images. Here, we aim to automate root image analysis with Artificial Intelligence (DCNNs), thus removing the bottleneck of image analysis. Read more.
Bo Peters, Juergen Kreyling (both University of Greifswald) and I lead the subproject ‘Roots’ within the large framework of the DIG-IT! Project.