University of Twente Student Theses


Tree Line Change in Majella, Italy: Trends, Causes and Predictions

Dai, Li (2010) Tree Line Change in Majella, Italy: Trends, Causes and Predictions.

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Abstract:High-altitude forests are sensitive to climate change, especially in the location of the tree line. In the course of 20th century, tree line change was observed in most parts of the world. This study aims to quantify the process and explain the causes of tree line change between 1954 and 2007 in 28.7 study area within Majella National Park, Italy, as well as predicting future changes. Dwarf pine (Pinus mugo L.) is the species dominates the tree line in the study area. Panchromatic aerial photos of 1954 and colour aerial photos of 2007 were accurately (weighted Kappa = 0.8) classified by the object-oriented method, and the change in the period was determined by map overlay. Vertical expansion was primary down slope. Most expansion was lateral and concentrated between 1700 and 2300 m elevation. Changes were analyzed for two plots, but only one plot was further analyzed for statistical modelling and prediction. Causes of dwarf pine expansion were inferred from logistic regression models implemented as generalized linear models in the R computing environment. Six explanatory variables showed significant relation to expansion: altitude, historical grazing, distance to historical beech, proximity to historical dwarf pine, 10 m neighbourhood effect of beech, and 70 m neighbourhood effect of dwarf pine. The model with these six variables successfully describes expansion (area under ROC curve is 0.87). Considering the variables identified for the final model, and the mostly lateral and downward change, expansion of dwarf pine in this plot was primarily driven by land use change, i.e. abandonment of alpine summer grazing. If the current trend continues, it is predicted to be a 47 m upwards shift of tree line by 2060 at the 0.6 probability threshold. Key word: tree line change, climate change, livestock grazing, dwarf pine, objectoriented classification, aerial photo, logistic regression, neighbourhood effect, R, generalized linear model
Item Type:Essay (Master)
Faculty:ITC: Faculty of Geo-information Science and Earth Observation
Programme:Geoinformation Science and Earth Observation MSc (75014)
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