Improved quantification of forest range shifts and their implications to ecosystem function in high-elevation forests - PhDData

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Improved quantification of forest range shifts and their implications to ecosystem function in high-elevation forests

The thesis was published by Morley, Peter James, in September 2022, University of Stirling.


Rapid environmental changes are driving shifts in forest distribution across the globe with significant implications for ecosystem function and biodiversity. Despite the prevalence of forest range shifts across the globe, reliable estimations of changes in forest extent and structure at the elevational treeline (the elevational limit of forest distribution) are difficult to obtain due to limited access to mountainous environments. Remote sensing data is well suited to quantifying environmental change across large areas; however, a lack of published research that uses remotely sensed data in studies of mountain forests has led to uncertainty surrounding how much information about forest structure at the mountain treeline can be resolved in remotely sensed data. This uncertainty presents a major obstacle to landscape-scale quantification of forest range shifts and estimation of the impacts forest advance will have on ecosystem function and biodiversity in mountain systems. The distribution of high-elevation coniferous forests in the Central Mountain Range, Taiwan, has changed rapidly with increases in treeline elevation and forest density reported. Climate is considered to be the primary regulatory factor of the treeline in the Central Mountain Range. However, topography modifies the response of treeline advance to environmental change resulting in a structurally diverse treeline. This research combines a network of field observations across the Central Mountain Range, Taiwan, with aerial photography and multispectral satellite imagery to 1) determine which spectral features derived from multispectral satellite remote sensing best explain variation in mountain treeline structure and the effect of sensor spatial resolution on the characterisation of structural variation; 2) quantify variation in rates of forest advance; 3) quantify the accuracy of forest change assessments using a sample-based area estimation and classifying spectral trends identified in a time-series of satellite remote sensing data, and 4) quantify changes in above-ground woody biomass. The results presented here show that the green, red and short-wave infrared spectral bands and vegetation indices derived from these spectral bands offer the best characterisation of vegetation structure across the treeline ecotone with R2 values reported up to 0.723. Sample-based change assessment using repeat aerial photography shows a 295.0 ha increase in forest area and a 115.1 m increase in the mean elevation of forest establishment between 1963 and 2016. The rate of forest advance is spatially variable with forest establishment occurring most rapidly on east and south facing slopes with gradients of 0-20° and is also temporally variable with the rate of forest establishment peaking between 1980 and 2001. The classification of spectral trends in time-series analysis shows that Landsat-based change estimates underestimate the area of forest advance in the Central Mountain Range. However, the general pattern and direction of habitat change are consistent with those derived from sample-based estimates of change using repeat aerial photography offering the opportunity for error adjustment. Consequently, the results presented within this thesis show a net gain in above-ground woody biomass of 4688.7 t C in areas above 2400 m a.s.l. in the Central Mountain Range, Taiwan, and a reduction in the area of alpine grassland. The methods presented in this thesis provide a major opportunity to improve the quantification of forest range shifts across mountain systems allowing the estimation of landscape-scale impacts of forest advance on biodiversity and ecosystem function in data-poor mountain regions.

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