This position is opened at Q-Forestlab (UGent) in the framework of the Belspo research project AFRO-CARDS: “African Forest RecOvery and CArbon Dynamics monitoring through Remote Sensing”.
About Ghent University
Ghent University is a world of its own. Employing more than 15,000 people, it is actively involved in education and research, management and administration, as well as technical and social service provision on a daily basis. It is one of the largest, most exciting employers in the area and offers great career opportunities. With its 11 faculties and more than 80 departments offering state-of-the-art study programmes grounded in research in a wide range of academic fields, Ghent University is a logical choice for its staff and students.
Your Tasks
Applications are invited for a postdoctoral research position in the field of vegetation modelling at the research group Q-Forestlab (UGent) in the framework of the Belspo research project: “African Forest RecOvery and CArbon Dynamics monitoring through Remote Sensing”.
At least 70% of your assignment will be spent on academic research.
Q-Forestlab (www.q-forestlab.ugent.be)
The laboratory of quantitative forest ecosystem science is a research unit at the Faculty of Bioscience Engineering of Ghent University, Belgium. The research unit is studying vegetation dynamics, carbon and water cycling in terrestrial ecosystems. Q-Forestlab has a broad interest in all types of terrestrial ecosystems, but currently has a strong focus on the ecology of tropical forest ecosystems, especially in DRCongo. Process-based vegetation modelling is the core research tool of the group, but the questions arising from the modelling work require dedicated field work activities. These field work activities are focused on improving uncertain process descriptions within vegetation models and on data-poor regions such as the Congo Basin.
Project
Context:
The Congo Basin plays a pivotal role in the global carbon cycle. However, increasing human disturbance due to the huge population expansion is generating large uncertainties in the regional carbon balance. This uncertainty mainly stems from a lack of understanding of forest regrowth trajectories. Objective: A fundamental gain in our comprehension of the recovery of the Congo rainforests and of its functions (functional biodiversity, carbon storage and sink) following slash-and-burn agriculture (here-after referred to as “post-disturbance”), to improve the ongoing and projected changes in the regional carbon balance of African tropical forests.
Research hypothesis:
Our central research hypothesis is that the recovery rates of carbon and functional diversity in regrowth forests are strongly affected by environment (climate and soil) and land-use history (past disturbances). However, we lack the fundamental understanding of the importance of those drivers to constrain current vegetation models. The lack of understanding these dynamics substantially undermines our capacity to assess and monitor the current and future regional (central African) carbon balance. We urgently need a step-change in our comprehension of the forest functioning post-disturbance, especially in a context of intensifying anthropogenic pressure and under a changing climate. Building this understanding is only possible through integrating forest observations at multiple spatial and temporal scales (from leaf traits to satellite remote sensing), coordinated with the development of Land Surface Models specifically calibrated on those ecosystems.
Methodology:
The consortium built for this STEREO project combines the unique expertise of multiple partners who have been working for decades on the Congo Basin. It will allow - for the first time - bridging the gap between empirical on-the-ground work, which is critical to understanding the underlying mechanisms, and satellite remote sensing, necessary to upscale and map the observed changes through a detailed proxy-sensing approach based on UAV (drone) monitoring. All those observations will feed Land Surface Models, which are the current gold-standard tool to project the fate of ecosystems in a changing world.
Expected outcome:
A state-of-the-art monitoring tool and products that assess landscape-level recovery dynamics across the basin; A new reference model for projecting the impacts of climate change and anthropogenic pressure on tropical forest functions.