Quantifying the response and sensitivity of tropical forest carbon sinks to various drivers

Project Rationale

Terrestrial ecosystems play an important role in the climate system and the global carbon cycle. For example, terrestrial vegetation acts as a carbon sink by absorbing up to 15-30% of all anthropogenic CO₂ emissions through photosynthesis [1]. This absorption regulates the buildup of CO₂ in the atmosphere, which in turn influences the levels of global warming and associated climate change. However, climate change and anthropogenic activities are threatening the role of terrestrial vegetation to act as carbon sink. Several factors (e.g., CO₂ fertilization, climate, nitrogen deposition, land use and land cover change, extreme climatic events etc.) have been identified as key variables that influence the ability of terrestrial ecosystems to act as carbon sink. However, there is currently uncertainty on the response of terrestrial ecosystem carbon sinks to the dynamics of these drivers [2]. Identifying factors that affect the capacity of the terrestrial vegetation to absorb carbon and quantifying the magnitude of their sensitivity to driving factors is important in accurately projecting future coupled carbon cycle and climate system. Therefore, this study aims to quantify the dynamics of tropical forest carbon sinks and their response and sensitivity to various environmental drivers.

Methodology

Recent studies are showing that the response of terrestrial ecosystems carbon sinks to various drivers differ greatly and remain uncertain [2,3]. However, to accurately project future carbon cycle and climate, there is need to better understand the response of terrestrial ecosystem carbon sinks to the dynamics of the drivers controlling these sinks. Firstly, this study will use a mix of in-situ data (e.g., from Flux Tower Sites), Earth Observation (EO) data and carbon exchange models to quantify the trends in tropical forest carbon sink in the past few decades. The study will then evaluate the response of the tropical forest carbon sinks to various drivers (e.g., CO₂ fertilization, climate, extreme climatic events nitrogen deposition, land use and land cover change etc.) using modelling and statistical analysis (e.g., machine learning/multivariate regression methods). The output from his study will provide information on the recent trends in tropical forest carbon sinks and elucidate their response and sensitivity to various drivers. Understanding how the tropical forests respond to various drivers is critical in reducing uncertainties in the projection of future climate.

Training

The INSPIRE DTP programme provides comprehensive personal and professional development training alongside extensive opportunities for students to expand their multi-disciplinary outlook through interactions with a wide network of academic, research and industrial/policy partners. The student will be registered at the University of Southampton and hosted at the School of Geography and Environmental Science. Specific training will include:

·        Earth Observation data retrieval, analysis, and interpretation

·        Machine leaning and statistical regression techniques

·        Carbon exchange modeling using diagnostic and prognostic models