Dr
Adriane Esquivel Muelbert investigates how forests respond to different global change forces and what the implications of these responses are on biodiversity and global biogeochemical cycles. Her work demonstrates the importance of drought tolerance in shaping diversity and composition across Neotropical tree communities and provides evidence that Amazonian forests are changing as a result of the increase in water stress and atmospheric CO
2. More recently, she has focused on tree mortality and how tree death varies across large geographical scales. In 2020, Adriane was winner of the Forests 2020 Young Investigator Award and lead for the successful International Tree Mortality Webinar series.
Adriane is part of the MEMBRA team which also includes
Bruno Cintra and
Rodrigo Bergamin. Their research has included lots of field work across the UK. The
MEMBRA project is about Understanding Memory of UK Treescapes for Better Resilience and Adaptation. It is a UK Treescapes project that looks at the memory of trees using cutting-edge molecular biology techniques to understand how past stresses are maintained and transmitted through generations.
Adriane is part of the
SynTreeSys project, which aims to understand the drivers of tree biodiversity across the tropical Americas and assess the extinction risk of different tree species across the region.
Adriane also recently started a NERC-NSF funded research project called GIGANTE. The project highlights are to improve our understanding of the ecology of giant tropical trees (≥50 cm diameter), which play a disproportionate role in carbon cycling and ecosystem functioning and improve the accuracy of global carbon dynamics modelling and learn from a global community of experts in tropical forest ecology, providing opportunities for creating a global network.
Dr
Liling Chang's main research interest is to examine responses of terrestrial ecosystems to climate change, elevated atmospheric CO2, and disturbance events (fires, droughts). Her research focuses on integrating field observations, remote sensing data, and process-based models to quantify and predict ecosystem water, energy, carbon fluxes, productivity, and demography.