Image: Ive van Krunkelsven
Image: Ive van Krunkelsven
Research project The project aims to increase our understanding how wood ants will influence carbon storage in soil and how climate change will affect their distribution in Arctic ecosystems. This project builds on detailed studies of ants, soil and vegetation interactions in mountain heaths and mountain forests in the Abisko region. The results will further be scaled to larger areas using images from drones and artificial intelligence.
The project is financed by Formas.
A warmer climate is fast changing Arctic ecosystems and risks to increase greenhouse gas emissions from Arctic soils. The mechanisms behind these increased greenhouse gas emissions are often related to soil living organisms that thrive in warming temperatures and can break down organic matter stored in Arctic soils. Few studies have investigated how larger soil organisms such as ants are contributing to this decomposition of organic carbon and act as ecosystem engineers that are affected by a warming climate.
Ants (Formicidae) are an example of such ecosystem engineers that can potentially spread in large areas of the Arctic and the Swedish mountains due to a warmer climate. How this will influence carbon storage in soil and ecosystem carbon dynamics is still unknown.
This project aims to increase our understanding how wood ants will influence carbon storage in soil and how climate change will affect their distribution in Arctic ecosystems. This project builds on detailed studies of ants, soil and vegetation interactions in mountain heaths and mountain forests in the Abisko region. The results will further be scaled to larger areas using images from drones and artificial intelligence. In detailed field studies we will measure how ants affect soil and vegetation parameters along an elevantion gradient.
We will use drones with multispectral and thermal cameras to map ant mounds and how they influence vegetation productivity. This allows to map the distribution in large areas and to develop a model that can predict the distribution and activity and landscape scale. These models will help to predict the spreading of ants in a warming Arctic.
This will be combined with machine-learning to derive actual maps of the effect ants have on soil and vegetation. The projekt will help us understand how soil living organisms like ants influence the ecosystem carbon balance, but also how these kind of processes and organisms can be inventoried.
