Landscape-Scale Variability in the Composition, Growth and Pattern of Alpine Treeline Vegetation
The productivity and distribution of northern and alpine plant species are predicted to increase and advance upslope and northwards in response to climate warming, particularly across the treeline ecotone. However, responses to warming in the past century have been highly variable, especially in regions with complex topography. In order to improve predictions of future change, I used field surveys, dendrochronology, and remote sensing to characterize variability in plant community composition, woody plant growth, and tree spatial patterns across treelines in a range of topographic settings. I then attempted to explain this variability using measured edaphic, climatic, and topographic variables. I found substantial differences in community composition, woody plant growth, and treeline ecotone abruptness between north and south-facing slopes. Shallow active layers and cold soils on north-facing slopes resulted in low shrub cover and slow rates of woody plant growth. The comparatively high cover of tall deciduous shrubs on south-facing slopes, in turn, restricted tree seedling establishment and resulted in relatively abrupt treeline ecotones. Trends in tree growth and the degree of clustering between tree stems varied between mountain ranges with different slope angles. Rapid spring runoff in steep valleys likely caused a spring soil moisture deficit that curbed tree growth over the past several decades, while high exposure to damaging winter winds in shallow valleys resulted in clustered patterns of tree stems. My findings suggest that changes in treeline vegetation over the next century will depend not just on rising air temperatures, but also on edaphic variables, wind exposure, snowpack dynamics, and tree-shrub interactions. Given that much of the landscape-scale variability in the composition, growth, and pattern of treeline vegetation can be attributed to slope aspect and angle, I recommend that these factors be included in predictive models of future vegetation change.