| Summary: | Abstract Spatial structure of habitats has been found to affect the species abundance and distribution patterns in heterogeneous environments. In this thesis, I studied landscape responses of the Siberian flying squirrel in a boreal forest context in northern Finland. Studies were conducted at several spatial scales in order to identify landscape characteristics that are associated with the species occurrence at a local scale and its distribution patterns at a regional scale. Data on species presence and absence in forest areas were collected in the field. Habitat patterns in landscapes were analysed from satellite images and landscape metrics concerning landscape structure were quantified in Geographic Information Systems (GIS). Results of this study are in agreement with the general landscape ecological theory and findings in the field. In northern Finland, the distribution of the Siberian flying squirrel primarily follows the spatial extent of spruce-dominated forests but that its actual occurrence is dependent on the scale of observation and the habitat structure. At a home range scale the abundance of deciduous trees in old spruce forest increases the probability that a forest site is occupied by the species, whereas at a local scale the amount of such spruce forests and linkages between habitat patches play an important role. At a regional scale, an increase in open areas and the dominance of pine makes the habitat unsuitable and restricts the presence of the species. Findings of the present research forward practical forest management planning at a large scale and may help set general conservation goals for the Siberian flying squirrel. When managing the species in a complex network of habitat patches in heterogeneous landscapes, spatial dispersion of potential habitat patches as well as connecting habitat and their temporal development should be considered carefully. For this purpose, remote sensed images and GIS are valuable and useful tools. Satellite-image based landscape analysis is presently ...
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