Peter Morley

PhD Student

Supervisor: Prof Alistair Jump

Start Date: 1st October 2015

3V1A Cottrell Building
Biological & Environmental Sciences
Faculty of Natural Sciences
University of Stirling
Stirling, Scotland, FK9 4LA

Tel: +44 (0)1786 467839
fax: +(44) 1786 467843

Research Project

Predicting changes in forest form and function in a tropical mountain region

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.


In comparison to temperate and boreal regions, forests in tropical mountain areas have been little studied and hence are poorly understood. There is limited data quantifying how tropical montane forests have responded to climatic change to date, limiting our ability to predict the impact of future climatic change on tropical montane forest distribution and biodiversity and their associated ecosystem services.

Satellite imagery represents a useful tool for quantifying change in forest extent over a regional scale and is particularly attractive in mountainous regions where challenging topography makes in-situ data collection difficult. Treelines provide markers for tracking forest distribution from satellite imagery and, as their upper limit is often temperature limited, they are also excellent indicators of climatic change.

High altitude forests in the Central Mountain Range of Taiwan are generally dominated by Taiwan fir (Abies kawakamii) or Taiwan hemlock (Tsuga chinensis) with scattered populations of other species such as the Taiwan pine (Pinus taiwanensis) or Taiwan white pine (Pinus morrisonicola). Since forests at the treeline are near monodominant, ongoing climatic changes are predominantly reflected in changes in growth and establishment and ultimately spatial distribution of the dominant species instead of complex shifts in species composition.

Project aims

The project will utilise a combination of plot-level forest inventory data, time series aerial photography, detailed topographical data and both medium and high resolution satellite imagery to assess localised changes in forest structure and distribution and use these to predict the extent of such changes across the Central Mountain Range as a whole. Plot-level and aerial photograph data will be used to determine the accuracy of remote sensing data when used to discriminate present day forest demographics at the local scale. The remote sensing data will then be scaled up across the Central Mountain Region to identify current and predict future forest range expansion and estimate the impact shifts in distribution will have on forest structure and function at a landscape scale. The research project can be split into the following topics:

Discriminating forest stand demography using high-resolution satellite imagery
In mountainous regions remote sensing data can offer an extremely useful tool for classifying forest structure and extent in remote areas. Due to the high topographic variability overhead images may misrepresent vertical changes in treeline. Assessing the accuracy of such data at different resolutions will be key to exploiting remote sensing data in mountainous areas. GIS will be used to combine forest inventory data with time series aerial photography to ground-truth satellite imagery and identify present day demographic structures. In validation we will determine the accuracy of high and medium resolution satellite imagery to discriminate between different stand demographics indicative of forest range expansion or stasis.

Tracking historic changes that led to current demographic structures
Significant shifts in treeline and forest density in the Central Mountain Region have been tracked using aerial photography from the period 1975-2001, showing range expansion of conifer forests into high altitude bamboo grasslands. Though a network of test sites across the Central Mountain Region the historic changes in forest growth and establishment will be identified to inform how present day structures arose.

Quantifying regional distribution and structure in the present day and future scenarios
The structural classifications identified above will be combined with satellite imagery across a wider area of the Central Mountain Region to quantify the current range expansion or stasis. Whilst generalizations can be made regarding future forest distribution based on isotherms, topography and local environmental conditions have an important role in regulating forest distribution and form. In order to predict future shifts in forest distribution and form detailed topographic data and existing microclimate data will be used alongside the regional scale data to estimate future changes to forest extent and structure.

Forest expansion and local biodiversity
Future treeline advance to higher altitudes will result in a loss of alpine grassland area and fragmentation of the habitat. Utilising predictions of future forest distribution we will be able to quantify the loss and identify potential refugia of bamboo grassland habitat across the Central Mountain Range.

Forest expansion and carbon stocks
Climate change will alter tree growth rates as well as distribution of montane forests resulting in changes of the carbon stocking capacity of montane forests. Existing allometric data, wood density data and forest inventory data in conjunction with current and projected regional forest distribution will be used to estimate changes in forest carbon stocks in the high altitude areas of the Central Mountain Range.

Abies Kawakamii treeline in the Central Mountain Range, Taiwan.

 Abies Kawakamii treeline in the Central Mountain Range, Taiwan
 Abies Kawakamii treeline in the Central Mountain Range, Taiwan

Photo credit:  Sarah Greenwood & Alistair Jump

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