Quantifying Amazonian tree diversity using next generation technologies

Description

Most life on Earth is concentrated in the tropics, and recent estimates suggest South American contains 43% of all known tree species, with many of these species restricted to the Amazonian rainforest biome. Beyond the inherent value of this enormous diversity, these forests also store and absorb vast quantities of carbon, thereby slowing climate change. As a result, understanding how these tree communities are responding to global change represents both a major challenge and a key research priority. Initial analyses suggest that the taxonomic and functional composition of Amazon forests may be changing in response to climate change¹. However, these results remain deeply uncertain because: 1. Amazonia is vast and inaccessible and therefore remains spatially under sampled, and 2. Identifying trees to the species level is extremely challenging using traditional botanical approaches^2,3.

In this project, the student will have the opportunity to undertake extensive fieldwork in Amazonian forests and leverage exciting new technologies (including leaf-level spectroscopy, UAV-based imaging spectroscopy and satellite remote sensing) alongside existing forests plots to develop new approaches to quantifying Amazonian plant diversity at large spatial scales. Drawing on these approaches, the student will have the opportunity to explore and expand questions such as:

• Why are some species of tree able to dominate Amazonian forests while others remain rare?
• Are dominant species as common and widespread in Amazonia as we believe?
• To what extent can spectroscopy be used to determine the functional profile of Amazonian tree species?
• What determines the landscape scale distribution of dominant Amazonian tree species?

This position is closely tied to the NERC fellowship of Dr Draper, and will involve substantial fieldwork in Amazonia, with opportunities to conduct fieldwork in Brazil, Peru, and/or French Guiana and any language skills in Spanish, Portuguese or French would be advantageous. We welcome applications from highly motivated students with strong quantitative skills. Familiarity with coding in R/Python is a major advantage and a willingness to undertake fieldwork in challenging tropical environments is essential.

Candidates are encouraged to contact Freddie Draper: f.draper@Liverpool.ac.uk, if they have further questions about the project.