Summary: | Several studies indicate a long-term decline in the numbers of voles in northern Fennoscandia. Altered land use and forest management practices have been proposed as possible causes of the decline. This doctorial thesis aimed to identify, on different spatial scales, landscape patterns that are important for the abundance of small mammals and that might be related to the decline. General trends and aspects of spatial habitat modelling were reviewed. Trapping data from three large extent monitoring programs were related to habitat factors on different spatial scales. For these analyses, a broad range of statistical and GIS (geographic information system) related methods was applied. On the microscale (trapping station, extent <= 10 m) and mesoscale (transect, length 90 m), structural habitat factors such as coarse and fine woody debris, umbrella vegetation and structural complexity of the forest floor were identified as important factors influencing small mammal abundance. Small mammal densities were related to the percentage landcover of vegetation types on the micro-, meso-, macro- (subarea/landscape, 1 x 1, 2.5 x 2.5 and 2 x 5 km) and regional scale (overall study area, 20 x 20 - 80 x 80 km). The spatial continuity (non- fragmentation) of old-growth pine forest patches on the landscape scale was positively related to the abundance of C. rufocanus, the species that showed the most pronounced long-term decline in numbers. The results of this thesis strongly suggest that altered land use might indeed be involved in the decline in numbers of voles in managed forest areas in northern Fennoscandia. To reveal and test responses of small mammals to changes in landscape patterns in more detail, this work proposes further application of large scale approaches. These approaches, e.g. the GIS-based prediction of the areas with currently high abundance of C. rufocanus can be tested by field sampling of the type applied in this thesis. Such approaches should consider the key aspects identified in the reviews on GIS-based ...
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