Quantifying and predicting the response of forest distribution to on-going climatic changes requires accurate data on species distribution and forest composition. Such data are typically gathered from plot-based forest inventory surveys. However, this approach is extremely limited in areas with poor access or difficult terrain. Consequently, there is poor data availability and hence little understanding, of how tropical mountain systems will respond to climate change.
This significant knowledge gap has major implications for our ability to predict future impacts of environmental change from global to local scales and for factors spanning from biome distribution and carbon economy to local biodiversity and ecosystem services.
Focusing on the montane tropical forests of Taiwan’s Central Mountain Range, my research aims to combine plot-level forest inventory data with aerial photographs and high resolution remote sensing data to derive new methods for conducting and interpreting forest assessments in less accessible regions.
Supervisors: Prof. Alistair Jump, Prof. Danny Donoghue and Dr Thiago Silva
Industrial partner: Guan Sheng Ecosystem Ltd.