Name: Erin Iona Megan Stoll

Project Title: Quantifying and predicting soil responses to rapid forest change in a tropical mountain region

Cohort: 2017/18

Institution: University of Stirling




Despite an abundance of data quantifying and predicting the response of forest distribution to on-going climatic changes in temperate and boreal regions, there is a near absence of data, 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. This project will be the first to combine plot-level forest inventory data with aerial photograph time series and high-resolution remote sensing data to quantify and predict below- ground changes associated with rapid shifts in tropical mountain forest distribution. The project will integrate existing data with field-based research and would suit students from a wide range of backgrounds, spanning from geography, through ecology to environmental science. An enthusiasm for fieldwork in mountain terrain and for understanding pattern and process at contrasting spatial scales is a must, however.


  1. To determine how different forms of forest advance impact the structure and composition of mountain soils.
  2. To identify the principal differences in nutrient cycling and decomposition rates as treeline advances.
  3. To use existing land cover classifications to scale up plot-level below-ground data to the regional scale.
  4. To combine regional scale estimates of below ground changes with existing data on forest distributional change to predict future carbon sequestration potential across the Central Mountain Region of Taiwan.


Project is funded by the Natural Environment Research Council and the University of Stirling as part of the IAPETUS Doctoral Training Partnership and conducted in collaboration with Durham University, UK and National Pingtung University of Science and Technology (NPUST), Taiwan, and is a CASE project with Indufor Asia Pacific.

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