Assessing Amazon forest vulnerability and resilience to dry periods across soil moisture and microenvironmental gradients
Amazon forests are important for global climate and biodiversity. However, major uncertainties remain about how they will respond to future climate, limiting our ability to make accurate projections and set conservation priorities. A critical but neglected area is the effect of soil water availability on forest drought responses.
Research has focused on deep water table forests (where groundwater is deeper than most tree roots),
leaving shallow water table forests (where roots have easy access to groundwater, comprising ~50% of the Basin) understudied. Climate-change-induced droughts can cause widespread tree mortality and large carbon emissions in deep water table regions. Yet emerging results indicate that shallow water table forests may be more resilient to drying, which increases the length of the growing season. Could enhanced productivity of shallow water table Amazon forests under drier conditions offset carbon losses projected for deep water table areas?
This PhD will investigate how soil water availability influences Amazon forest responses to seasonal dry
periods (and droughts, if observed). You will analyse key indicators of forest carbon—vertical leaf area
distributions (from lidar) and tree growth (from dendrometers)—and test potential drivers, including soil moisture, tree hydraulic strategies, and microenvironment. The PhD project will be embedded within a large international research team with established forest sites in the Brazilian Amazon. You will analyse existing datasets in combination with making new, complementary measurements including ground-based lidar, sapflow, and tree hydraulic traits during a 12-month field campaign. While in Brazil, you will undertake a placement at the Federal University of Amazonas (UFAM), developing skills in lidar data collection and analysis, and ecohydrology.
You will develop expertise in fieldwork, ecosystem science and ecohydrology, advanced data analysis and
statistics, remote sensing, and international collaborations. This project is well positioned to initiate an
exciting and impactful career in environmental science.
Applicants should hold a minimum of a UK Honours Degree at 2:1 level or equivalent in subjects such as Ecology, Forestry, Botany, Natural Sciences, Environmental Science, Geography, or Biology. Experience of fieldwork within tropical forests, remote sensing, and writing computer code (e.g. R) would be advantageous. Proficiency in, or willingness to learn, Portuguese (or proficiency in Spanish) is also desirable.
For further details please contact Dr Marielle Smith (firstname.lastname@example.org).