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Being behind the times? Assessing the liana-induced impact on forest phenology using a multispectral Unmanned Aerial System (UAS)

Tropical forests are a major global carbon sink and account for a third of the carbon fixed globally by photosynthesis. Recent research shows that these forests are changing, including increases in abundance and biomass of lianas (woody vines), which may be a result of changing climatic conditions. Lianas reduce growth and increase mortality of their host trees, thereby reducing carbon accumulation in tropical forests by as much as 76%. Increased liana dominance may therefore further reduce carbon uptake and storage and endanger the future of the tropical carbon sink, with serious implications for climate change. Tree canopies suffer from liana infestation, which limits their leaf productivity and leaf area and their reproductive success. Nevertheless, liana-induced impact on phenological processes has received little attention, but is crucial to i) accurately include liana effects in vegetation models and ii) better predict of the fate of tropical forests both due to climate change as well as liana propagation in the future. This project aims to:

  1. Determine whether liana infestation reduces the photosynthetic capacity of their host trees, and
  2. Test whether the presence of lianas affect the timing of main phenological processes in the forest, such as leaf fall, leaf flush, fruiting and flowering.

The project will involve a year-long field campaign in Panama to collect imagery using an Unmanned Aerial Vehicle (UAV) and an analysis of remote sensing data to derive information on photosynthetic capacity and timing of phenological events in the forest. The student will work with a collaborative supervisory team, composed of physical geographers and ecologists from the School of Geography, Smithsonian Tropical Research Institute, Panama, and Marquette University, US.

The applicant should be willing to spend time in a relatively isolated area in Panama to collect field data and to learn advanced statistical modelling and remote sensing techniques. Ecological field experience is an asset, but an enthusiasm for nature and tropical forests is by far the most important prerequisite. Applicants should hold a minimum of a UK Honours degree at 2:1 level, or equivalent, in a subject such as Physical Geography, Environmental Science, Ecology or Natural Sciences.

For further details please contact Dr. Doreen Boyd (doreen.boyd@nottingham.ac.uk) or Dr. Geertje van der Heijden (geertje.vanderheijden@nottingham.ac.uk).