Are you looking for an exciting PhD opportunity working on globally significant research questions in tropical ecosystems? Are you able to combine extensive fieldwork with spatial analytical techniques? Do you want to work in collaboration with an international team?
Climate change and human impacts are causing alarming increases in the occurrence of fires inside tropical forests. As tropical moist forest trees have been virtually immune to fires at evolutionary timescales, fires cause high levels of tree mortality resulting in biomass and species losses. The extent and timescale of the recovery of forest carbon and species composition, and how this varies across different tropical regions, is hampered by a severe lack of data. This project will address this knowledge gap in the global carbon budget by:
- carrying out field surveys of previously burnt forests to gain the longest records of tropical forest recovery from fire (Ghana and Borneo)
- collating published datasets to supplement field data, comparing the extent of forest recovery over multiple decades at multiple locations in at least three continents (Africa, Asia, South America)
- using remote sensing to upscale results on carbon stock lost after fire and its recovery over time.
The project will involve collaboration with researchers at the Forestry Research Institute of Ghana, Ghana Forestry Commission, Universiti Brunei Darussalam, University of Lancaster, and University of Leeds.
You will gain practical and leadership skills while carrying out international field work the tropics. You will develop high-level analytical skills working with large field and remote sensing datasets utilising state of the art integrated computing tools such as R, Google Earth Engine, and GIS. You will develop skills in project management. You will learn how to produce scientific papers of the highest quality, and will be expected to present globally important research at international conferences. You will interact with leading researchers and develop a global network of collaborators.
Although closed canopy tropical forests are historically only weakly flammable, due to fragmentation, logging, agricultural impacts, and climate change, the number of wildfires extending into closed canopy forests has increased globally (Cochrane 2003). Tropical forest tree species are not well adapted to fire, and post-fire mortality rates of up to 90 per cent have been observed. This causes a large release of carbon emissions into the atmosphere from the combustion of wood and litter, and the eventual decomposition of dead biomass. Recent fires in the Amazon are thought to have released more carbon than from all tropical deforestation combined (Aragão et al. 2018). A key question is whether these forests can regenerate in terms of biomass and species composition, and the timescale of this recovery. This is highly relevant to the carbon cycle, and therefore global climate.
A number of studies have assessed post-fire recovery, but the majority studies have very short timescales (<5 years, exceptionally 9-15 years, Slik et al. 2002, Slik et al. 2008, Barlow and Peres 2008). All of these studies show negative impacts of fire, but longer timescales are necessary to address the full impacts on biomass and species composition. An as-yet unpublished dataset collected by the primary supervisor details recovery of Ghanaian forests from fires which occurred during the 1983 El Niño event and measured 27 years later. This data showed positive signs of regeneration with a range of 15-70 years for full recovery of forest structure. Intriguingly, recent work by Silva et al. (2018) showed recovery of Amazonian burnt forests had stalled when measured up to 30 years post fire. It is possible that African forests, which may have experienced greater fire occurrence in their evolutionary history, are more resilient than Amazonian forests where the climate is generally wetter. This study will extend Ghanaian and Bornean post-fire records to reach 37 years after fire, and collate datasets from the literature to enable a multi-continental comparison of recovery with the longest records to date. These ground datasets will be used in remote sensing analyses to scale up forest carbon loss and regrowth data across much larger focal study areas.