Understanding the vulnerability of intact Amazonian forests to climate change through the integration of remote sensing and field data

About the Project

Lead Supervisor and Department: Pablo Sanchez-Martinez, Grantham Institute and the Department of Life Sciences

Co-supervisors: Jesus Aguirre, Imperial College of London, Department of Life Sciences; Patrick Meir, School of Geosciences, University of Edinburgh

Amazonian forests are increasingly exposed to drier and warmer conditions, which are expected to affect their function and stability. However, the impacts of drought on these forests are still far from fully understood. The vast diversity of these forests and the limited, scattered field data available make this situation difficult to assess. The emergence of high-resolution remote sensing in recent years has opened the door to establishing stronger links between time series from satellite-borne sensors and field measurements, allowing us to better understand different dimensions of forest vulnerability related to tree physiological thresholds, forest structure, and biodiversity, as well as the risks these forests face under climate change.

In this project, we aim to establish connections between remote sensing products and forest ecological data to better understand forest vulnerability to climate-driven mortality. This new information will contribute to developing tools that will enable forest stakeholders and policymakers to assess the conservation and restoration actions needed to preserve these ecosystems and the services they provide.

Responsibilities

• Produce a PhD thesis on the research topic which will have to be submitted to the department of life sciences by the end of the studentship (i.e., March 2029).
• Contribute to the development of a high-resolution tree mortality algorithm based on multispectral remote sensing (Planet Labs, Sentinel-2) aiming to separate standing death from gap formation.
• Contribute to development of new methods to predict and map functional strategies and physiological/structural stress for highly diverse ecosystems such as Amazon forests.
• Perform validation both on mortality and functional strategies mapping using available and newly-developed field observations.
• Conduct spatial-temporal analyses on the relationship between functional strategies and tree mortality incidence.
• Build a framework of tree mortality risk to climate change specially focused on canopy trees
• Undertake comprehensive and systematic literature reviews.
• Contribute to wider project planning, participate in fieldwork related to the project.
• Write up the results of the research for publication in peer-reviewed journals and present the work in national and international conferences and public meetings.
• Represent the research group at external meetings/seminars, either with other members of the group or alone.
• Collaborate openly and closely with allied researchers in the projects supporting this PhD as part of a wider team.

Essential selection criteria

• A Master’s degree in Ecology, Biodiversity, Environmental Science, Remote Sensing, Data Science, or a related field.
• Strong quantitative and programming skills (R required).
• Interest in tropical ecology and climate change mitigation.
• Experience with GIS and remote sensing.
• Proficient in written English.
• Ability to manage own research activities and be research independent but be able to follow advise and behave as a team member and collaborate with a multi-site supervisory team.
• Excellent communication skills, including the ability to write text that can be published, present data at conferences, and represent the research group at meetings.
• Is committed to advancing diversity and inclusion.

Desirable selection criteria

• Experience of actively collaborating in the development of research articles for publication.
• Background in working with ecophysiology/functional ecology.
• Interest in using art as a way to explore science communication.
• Fieldwork experience is desirable, ideally in the tropics.
• Communication skills in Portuguese are desirable