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Understanding Differences in Thermal Sensitivity Across Amazonian Tree Species

Dr David Galbraith (SoG), Prof Emanuel Gloor (SoG), Prof Christine Foyer (SoB)

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Project Summary

Tropical forests play a critically important role in the Earth System by regulating climate and housing unparalleled biodiversity.  Their functioning, however, is fundamentally dependent on temperature, which exerts considerable influence on a range of plant processes from photosynthesis to reproduction and ultimately forest carbon storage and species composition.  Temperatures over tropical regions have been rising steadily (Gloor et al. 2016) and there are fears that future high temperatures may considerably impair forest functioning and even result in large losses of forest area under some very warm scenarios (e.g. Galbraith et al. 2010).  However, despite its critical importance, there is almost no empirical data available on the thermal sensitivity of tropical forests to high temperatures, fundamentally limiting our ability to simulate climate change impacts on tropical forest biogeochemistry and land surface-climate feedbacks.  

With recent funding (NERC and Royal Society), we have installed a tower in a rapidly warming southern Amazonian site to monitor temperatures (Figure 1) of individual tree crowns. We will also replicate this set-up in a tower in western Amazonia.  In this study, you will build on these efforts by conducting additional field measurements, experiments and/or ecosystem modelling work to better understand how different Amazonian tree species vary in their sensitivity to higher temperatures.

Potential research questions include:  1) What drives variation in leaf temperatures across Amazonian species (i.e. Why do some taxa exhibit high leaf temperature departures from air temperature but others not?),  2) Do taxa which show high leaf-to-air temperature differences have broader photosynthetic temperature optima and lower increases in respiration with increasing temperature? 3) To what extent are plant physiological processes able to acclimate to increasing temperatures and 4) What is the optimal thermal strategy for Amazonian plants in a warmer world?

To address question these questions, a range of approaches are necessary.  Variation in temperature across taxa may be related, for example, to differences in plant water use strategies, with high evapotranspiration having a cooling effect on leaf temperatures.  To evaluate this effect, sap flow sensors will be installed for each of our target trees in both of our study sites.   To better understand key physiological responses to thermal stress, temperature response curves for both photosynthesis and respiration will be performed, while acclimation responses will be investigated using experimental organ-scale warming studies.  Finally, impacts of warming on the future functional composition of Amazonian rainforests will be evaluated using an ecosystem modelling approach (Fyllas et al. 2013).

Methodological Approach

This PhD project will be interdisciplinary in that it will involve a range of approaches.  These will include analysis of crown-level thermal images and meteorological data as well as physiological measurements (e.g. respiration, photosynthesis, sap flow).  The student will tap into an ongoing project in southern Amazonia (BIO-RED) and thus will collaborate actively with colleagues in Brazil and Peru.  The ecosystem modelling component will focus on making projections of how plant functional composition may shift under future warming scenarios using an individual-based forest simulator (TFS – the Traits-based Forest Simulator).  Depending on the specific angle undertaken, there may also be scope for experimental warming of leaves and other plant organs (e.g. reproductive structures).

Stitched Thermal Image from Canopy Tower in Nova Xavantina, Brazil.


You will work under the supervision of Dr. David Galbraith, Prof. Emanuel Gloor and Prof. Christine Foyer and receive specific training in the skills required for this project (e.g. thermal image analysis, physiological measurements, ecosystem modelling).  You will be based in the Ecology and Global Change research cluster in the School of Geography, which has a long-standing record of cutting-edge research in tropical ecosystems.   You will be working on a topic of significant global relevance of wide scientific and societal interest. 

Student Profile

We are looking for a candidate that thrives in a multidisciplinary context.  You should have a good grounding in natural or physical sciences and a strong interest in tropical ecosystems.  Ability to spend long periods of time in the Tropics is essential, often in difficult conditions.  You should also be highly quantitative, with an aptitude for programming, given the modelling component of the work.  Previous experience in a tropical setting and some familiarity with scientific programming (e.g. R, Matlab, Java) would be advantageous.


Galbraith, D., Levy, P., Sitch, S., Huntingford, C., Cox, P., Williams, M. and Meir P. (2010) Multiple mechanisms of Amazonian forest biomass losses in three dynamic global vegetation models under climate change. New Phytologist, 187: 647-665.

Gloor, M, Barichivich, J, Ziv, G, Brienen, R, Schöngart, J, Peylin, P, Ladvocat Cintra, B, Feldpausch, T, Phillips, O, Baker J.  Recente Amazon climate as background for possible ongoing and future changes in Amazon humid forests.  Global Biogeochemical Cycles 29:1384-1399.

Fyllas, NM, Gloor, EU, Mercado, LM, Sitch, S, Quesada, CA, Domingues, TF, Galbraith, DR, Torre-Lezama, A., Vilanova, E, Ramirez-Angulo, H, Higuchi, N, Neill, DA, Silveira, M, Ferreira, L, Malhi, Y, Phillips, OL and Lloyd J. 2014. Analysing Amazonian forest productivity using a new individual and trait based model.  Geoscientific Model Development,7:1251-1269.

Related undergraduate subjects:

  • Applied mathematics
  • Biodiversity
  • Biology
  • Earth system science
  • Ecology
  • Environmental science
  • Geography
  • Mathematics
  • Meteorology
  • Natural sciences
  • Physical geography
  • Physical science
  • Plant science