ASSESSMENT OF ECOLOGICAL CONDITIONS OF PERMANENT MEADOWS IN THE ITALIAN ALPS: LOSS, BIODIVERSITY AND REMOTE SENSING CHANGE DETECTION
Tesi di Dottorato
Data di Pubblicazione:
2011
Citazione:
ASSESSMENT OF ECOLOGICAL CONDITIONS OF PERMANENT MEADOWS IN THE ITALIAN ALPS: LOSS, BIODIVERSITY AND REMOTE SENSING CHANGE DETECTION / A.m. Teixeira Monteiro ; tutor: Marco Acutis ; supervisor: Stefano Bocchi ; coordinator: Graziano Zocchi. Universita' degli Studi di Milano, 2011 Feb 08. 22. ciclo, Anno Accademico 2009. [10.13130/teixeira-monteiro-antonio-manuel_phd2011-02-08].
Abstract:
The monitoring of ecological condition of grasslands ecosystems in the
European Alps is a main issue for mountain regions, since the abandonment of
traditional and sustainable management practices has exposed grassland habitat
to significant impacts in a context of global environmental change.
The present research project was focused in assessment of the state of
permanent meadows in the lowlands of Valtellina Valley (80 km2), Italian Alps,
during the timeframe 1980-2000. In specific, it quantified the land use/land
cover changes and identified main drivers behind permanent meadows loss;
characterized the relationship between biodiversity in the meadows and the
spatial-environmental conditions in the landscape and by last evaluated the use
of satellite remote sensing data for fast change detection in landscape. To
achieve such aims, the research project was organized in three different
approaches presented in the four chapters of this thesis.
Concerning the quantification of the land use/land cover and identification of
main drivers behind permanent meadows loss, the results show a strong
decrease in meadows (-18.5%) in a context of agricultural land decrease and
human settlements increase. This was the land cover type with highest loss and
conversion rate during the study period. Meadows were converted to human
settlements (urban, industrial and roads), other agriculture uses (cultivation,
orchard, vineyard), bushland and uncultivated land. Meadows loss occurred
mainly in soils with good land capability, low slope, exposed to south and in
proximity of roads, urban settlements and bushland. Densities of urban,
industrial and bushland and land capability were the only significant drivers for
meadows loss, while distance to meadow edge, meadows density, distance to
roads and soil degradation were the only significant drivers for meadows
preservation.
Concerning the characterization of the relationship between biodiversity in the
meadows and the spatial-environmental conditions in the landscape, the results
evidenced that species richness and Shannon indices were best explained by
regressive models including changes occurred in spatial environmental
heterogeneity from 1980 to 2000. Species richness was negatively related to
strong decrease in meadows habitat area and recent urban area, while Shannon
index was positively related to the increase in landscape diversity. In contrast,
species evenness was better explained by regressive model including recent
spatial environmental heterogeneity and positively related to increase ineastness in the study area, and negatively affected both by the area of woody
and soil pH (KCl).
Concerning the evaluation of the use of satellite remotely sensing data for land
cover mapping and change detection in landscape, the results show that the
hybrid approach for land cover classification based of Landsat imagery was
highly accurate. Image differencing is the technique which best detect changes
in landscape as well as in urban, meadow and bush land. The accuracy of
change detection was moderate.
This thesis concludes that the conflict by land in locations densely occupied by
other land cover types with good land capability is the major threat to
meadows and avoidance of fragmentation may be a good strategy for its
preservation. The meadows habitat needs a well-designed landscape and
farming planning, which should account the economic value of the ecosystem
services provided by this habitat. In addition, to conserve plant diversity in
meadows it is necessary to avoid loss of meadows habitat, maintain landscape
diversity and execute a sustainable meadow management.
Remotely sensed imagery can be a reliable source of information for alps,
although particula
Tipologia IRIS:
Tesi di dottorato
Keywords:
Land cover/land use changes ; Meadows loss ; GIS-based logistic regression ; Aerial photographs ; Italian Alps ; Species richness ; Shannon index ; Evenness Grassland; Landscape metrics; Stepwise regression; European Alps; Valtellina Valley; Image differencing; Image regression; Hybrid classification; Remote sensing;
Elenco autori:
A.M. TEIXEIRA MONTEIRO
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