W. Towers

Landscape-scale vegetation change in the Cairngorms, Scotland, 1946-1988: implications for land management

Abstract Land cover change data were derived from interpretation of aerial photographs taken in 1946 and 1988 for 1000 km2 area of the Cairngorms area, Scotland. These data are compared with qualitative predictions based on the successional models of Miles (1985 J. Soil. Sci., 36). The impacts of man are shown to have been of the greatest magnitude, with conifer planting showing the greatest net increase in area between 1946 and 1988. Successional changes in seminatural vegetation did occur but none totalled more than 5 km2. Areas of semi-natural woodland were already scarce by 1946, but the extensive areas of heather also showed few successional transitions to other communities, such as grassland, scrub or woodland. The findings are discussed in relation to changes in land use and herbivore densities over this time period. The theoretical successional framework of Miles (1985), with the important addition of the more direct effects of man, is shown to be a valuable tool for the examination of vegetation change data and the implications for management in an area such as the Cairngorms.

The Risk of Peat Erosion from Climate Change: Land Management Combinations—An Assessment with Bayesian Belief Networks

ABSTRACT Modeling risk factors to soils is constrained by the lack of key data and understanding that explicitly and quantitatively link specific threats to risk. Peat erosion results from the complex interaction of climatic, topographic, and anthropogenic influences acting over a long period of time. With numerous contemporary factors operating to perpetuate the erosion processes, it is often difficult to identify with certainty what actually are the initial and subsequent drivers of erosion. In this situation, expert opinion forms a vital source of information. Here we demonstrate how Bayesian Belief Networks (BBN) can be used to combine quantitative data from the National Soils Inventory of Scotland (NSIS) with qualitative expert knowledge to estimate risk of peat erosion in Scotland. This model was used to identify the main factors associated with peat erosion. It was shown that climatic variables (increased temperature, decreased precipitation) are the most important risk factors for perpetuating peatland erosion. However, the BBN approach also indicated that maintaining good vegetation cover is a significant mitigating factor. It would follow that land management practices that impact negatively on vegetation cover would also exacerbate peatland erosion given a hot dry climate.

Modelling native woodland potential in the Scottish uplands.

It is estimated that native woodland cover in Scotland has been reduced to less than 5% of its original area. Restoration of the native woodland resource is now a conservation priority as expressed, for example, in Habitat Action Plans (HAP). Research undertaken by Scottish Natural Heritage (SNH) (Ratcliffe et al., 1998) has demonstrated that the spatial distribution of new woodland can have a major impact on its value for biodiversity and conservation. This paper describes the data and methodology underpinning the Native Woodland Model (NWM) and its application to help SNH meet a number of its objectives, including the development of Forest Habitat Networks (FHNs).