Nitrogen cycling in arctic ecosystems: at present and in future

Main area:Ecology
 
Target group:Biology, Bioinformatics
 
Educational level:Masters
 
Project description:

The Arctic is warming at approximately twice of the global rate rates and plants growing in this region are expected to undergo large changes (species turnover, increase of greenness) in response of climate warming. There is strong vegetation gradient within the Arctic: from southern forest zone to the polar desert zone and modelled vegetation distribution (as well as carbon budget) in this vast area is often/only determined by air temperature. Many other factors than temperature, e.g, soil moisture and acidity, nitrogen (N) availability, could also have strong impacts on vegetation distribution. In this thesis work, we suggest to mainly looking at N cycling in arctic ecosystems and quantifying the effects of N availability on plant productivity as well as distribution. A widely-used dynamic ecosystem model, LPJ-GUESS will be used as a platform to distinguish the role of nitrogen in arctic ecosystems at present and in future. Importantly, by using LPJ-GUESS, this work will be able to explicitly link plant N dynamics to vegetation shifting, increase of vegetation coverage as well as permafrost thawing (more carbon available for decomposition) under warmer climate. The work will start with summarizing field and lab literature to parameterize N in arctic plant functional types (PFTs) and soils in the model. Then, different model simulations (with/without permafrost feedbacks, with/without nitrogen limitations, as well as different degrees of warming) will be conducted to test how investigated factors interplay with each other in determine future ecosystem carbon budget for the whole pan-Arctic region. The extract information from this work will greatly improve the current prediction about sink and source functionality of the Arctic and as well as in predicting future climate changes. More information about LPJ-GUESS: http://iis4.nateko.lu.se/lpj-guess/resources.html

 
Methods used:Ecosystem modeling, data analysis, literature review
 
Keywords:nitrogen cycle, climate change, vegetation dynamics, permafrost, Arctic
 
Supervisor(s):  Riikka Rinnan, Jing Tang
 
Email:riikkar@bio.ku.dk