SD-25094 PHD IN RELATIONSHIP BETWEEN DROUGHT AND POLLUTANT DEPOSITION IN FORESTS

How will you contribute?

The increase of the frequency and intensity of droughts and heatwaves due to climate change will likely decrease the resilience of forests to cope with toxic atmospheric inputs (e.g., those of ammonia (NH3), but also ozone (O3)). Dry deposition fluxes of reactive nitrogen, including O3 are linked to transpiration and photosynthesis (stomata uptake and release), which are the result of supply-demand interactions (net radiation, atmospheric dryness, and soil moisture) and the ecophysiological response of trees. Additionally, climate change-induced trends in precipitation patterns are likely to modify the partitioning between wet and dry deposition nitrogen budgets.

This project aims to explore the signatures of stress episodes on the diurnal and seasonal variability of O3 and NH3 dry deposition fluxes to better understand the coupling between foliage responses and reactive trace gas fluxes in relation to supply-demand interactions. You will conduct a comprehensive literature review, employ mathematical modelling to formulate hypotheses, develop a research plan, use novel open data science techniques to evaluate a wide range of data, including statistical methods to test hypotheses. This will be based on combining existing state-of-the art field data sets of NH3-O3-CO2-H2O fluxes from different forests ecosystems in Europe with the application of big-leaf resistance models and drought indices under various meteorological conditions. You will explore the influence of biophysical characteristics (e.g. epicuticular processes) on the exchange fluxes and budgets at various timescales. Data science methods (e.g., information theory) will be used to identify interacting variables contributing to uptake resistances and drought signatures in the exchange fluxes. This will be complemented by field experiments to monitor the partitioning between dry and wet deposition and their dependency on the frequency of droughts and heat stress episodes in Luxembourg, to assess the interactive effects of changing air quality and climate on N deposition budgets. You will interact with your extended supervision team and other colleagues within FORFUS, FORLUX and LIST to address your own research questions and contribute to the research of others. You will explain and present your research internally and at international conferences, and publish papers, codes, and datasets resulting from your research.

You will follow the rules and curriculum set out by the Doctoral School in Science and Engineering (https://www.uni.lu/research-en/doctoral-education/dsse/) and engage in courses and activities organised by the doctoral training unit FORFUS.

Are you passionate about research? So are we! Come and join us

The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology Organization (RTO) active in the fields of materials, environment and IT. By generating relevant scientific knowledge and converting knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities in their decisions and businesses in their strategies.

To address the urgent societal need for science-based management recommendations for forests under increasing pressure, and to leverage on the fast-developing expertise in multi-disciplinary forest research in Luxembourg, LIST, in collaboration with the University of Luxembourg and the Luxembourg Institute of Socio-Economic Research, has formed a dedicated doctoral training unit (DTU) on “Forest function under stress” (FORFUS). It consists of 4 inter-linked research clusters, focusing on below-ground processes, tree and canopy processes, remote sensing observations, and prediction and valuation of forest functions, providing a holistic view on forests as complex systems. See the project website to find out more about the FORFUS doctoral training unit: here

Do you want to know more about LIST? Check our website: https://www.list.lu/

Is Your profile described below? Are you our future colleague? Apply now!

Education

 You hold a MSc or equivalent in Meteorology, Chemistry, Environmental Science, or a related discipline in the Geosciences

Experience and skills

You have a strong interest in the interaction of air quality, climate and the biosphere. A background in micrometeorology would be ideal but is not required. Experience in data science methods or artificial intelligence would be a strong asset.

You enjoy both data analysis and field observation. Scripting and programming experience are essential.

You like working in a team, explaining and presenting research ideas and results.

Language skills

Very good level of written and spoken English.