Title:
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Dynamic feedbacks between landform, landscape processes and vegetation patterns : a modelling framework to predict the distribution of plant species in Lefka Ori, Crete, Greece
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The aim of the thesis has been to describe and model
landforms and active landscape processes and include model
feedbacks and climatic parameters into plant species distribution
models. The study area has been an ecologically important
mountainous area, the Lefka Ori of Crete. Starting point has been a
number of previous studies underlying that climatic and geoenvironmental
factors are among the most significant controlling the
spatial distribution of rare and endemic species. The limitations of
past studies that this study tried to address were (a) some of these
factors are complex (e.g. landscape instability, mass movement), (b)
they do not refer to the landscape scale (e.g. erosion-deposition,
water redistribution) or (c) data are not available (i.e. climatic). To
achieve these aims: (i) Object Based Image Analysis was used to
create a geological map of the area, (i i) a set of land surface
parameters were created from elevation data, (iii) a semi-automated
method was developed to map the landforms of potential ecological
Significance, (iv) available climatic data were reviewed and satellite
imagery was utilized to address the climatic component through snow
cover persistence patterns, (v) a field experiment was set up for the
description of active landscape processes, (vi) dynamic landscape
process were modeled for water redistribution, erosionsedimentation,
landscape (in)stability and mass movement patterns.
In the course of the study 75 vegetation plots were sampled and
merged with another 80 from past stud ies leading to the formulation
of statistical models (GLMs) for 59 species. The resu lts show that
geology, elevation and snow cover persistence patterns explain most
of the variability for most species thus were more frequently included
in the predictive models. This signifies the climatic and geological
control over species distribution. For four species of conservation
importance model results were presented in detail leading to
probabilistic distribution maps.
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