About the Project
Amazon forests are global epicentres of biological diversity, being home to > 15,000 different tree species. These species are characterised by a large number of functional traits which ultimately underpin plant ecological strategies, positioning them along the fundamental axes of growth, survival and reproduction. In recent years, substantial datasets of functional traits have become available for Amazonian tree species, including foliar traits, seed traits, wood structural and anatomical traits and physiological traits closely associated with resistance to climatic stressors such as drought. This growing database of plant functional traits has the potential to yield substantial new insights into the structure and function of Amazonian forest communities, but has been little explored.
Although patterns of taxonomic diversity across Amazonia have been well documented, the functional richness and diversity of Amazonian forests is poorly known. A recent study along an elevational gradient in the Peruvian Amazon found that measures of functional richness and diversity were important predictors of stand-scale carbon cycling but the role of functional diversity in modulating forest processes over large spatial scales has never been evaluated. Community-level functional diversity may also enhance resilience of forests to climate stress. In temperate forests, for example, the community-level diversity in hydraulic traits has been shown to buffer forests against interannual drought. While functional diversity has been shown to enhance tropical forest resilience in model simulations, there have been no data-based investigations into the strength of this regulatory effect.
This project represents an exciting opportunity to advance our knowledge of how functional diversity is patterned across Amazonia and how this interacts with ecosystem functioning and resilience at a large scale. The volume of data available and the breadth of expertise in the supervisory team make the project very flexible, with the specific direction ultimately being determined by the interests of the student. The studentship could involve a combination of the following specific objectives:
1. Quantifying large-scale patterns in community functional diversity across Amazonian forests. This would involve reconciling datasets of species-level functional traits with data on forest community composition from across Amazonia to map single and multi-trait diversity metrics at a biome scale. This analysis would allow a first appreciation of the basin-wide inter-relationships between different groups of traits – e.g. leaf morphological traits vs. wood traits vs. hydraulic traits.
2. Examining the predictive strength of functional diversity vs. other descriptors of diversity (e.g. taxonomic diversity) as predictors of ecosystem processes in Amazonia (e.g. wood production, biomass storage).
3. Exploring the role of functional diversity in conferring resilience to drought. This may involve the use of an individual-based forest simulator now updated to include a mechanistic description of water transport through plants, parameterised with data from Amazonian forests.
Potential for High Impact Work
The questions addressed within this PhD are fundamentally important questions within tropical forest ecology and highly relevant for understanding the impacts of global environmental change on forest function and composition. Each of the objectives described above has the potential to yield high-impact publications which could significantly shape the field of research.
Training and Supervision
The student will work under the supervision of David Galbraith, Oliver Phillips and Emanuel Gloor in the School of Geography, University of Leeds. This project directly builds on data being collated within a NERC grant (ARBOLES:A trait based understanding of LATAM forest biodiversity and resilience) led by the PI team. ARBOLES is a consortium involving multiple partners in the UK and South America. This project thus offers the student the possibility to build research ties with a wide range of scientists at different career stages.
The student will have access to large datasets of forest traits and dynamics from across the Amazon. Training will include management and analysis of large datasets and individual-based ecosystem modelling. There may also be the opportunity for new fieldwork in Amazonia. The student will be based within the Ecology and Global Change cluster, a dynamic and world-leading research group focusing on tropical forest ecology and response to global change.
We welcome motivated students with a keen interested in tropical forest ecology. Students with strong quantitative skills are particularly encouraged to apply.
 ter Steege H, et al. 2013. Hyperdominance in the Amazonian tree flora. Science 342:1243092.
 Anderegg W., et al. 2018. Hydraulic diversity regulates ecosystem resilience during drought. Nature 561:538-541.
 Levine N, et al. 2016. Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change. PNAS 113:793-797.
 Fyllas et al. 2014. Analysing Amazonian productivity using a new individual and trait-based model. Geoscientific Model Development 7:1251-1269.
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