The acidity of Welsh soils

Abstract. The pH of soil surface horizons in Wales ranges from 3.5 to 7.5 and is significantly higher on agricultural land than under either rough grazing, unenclosed grassland or woodland. Sufficient information exists to map broad classes of soil pH. Rough grazing and woodland sites are concentrated on soil types which are naturally very acid. In Wales, such soils are found on the main mountain ranges and show up clearly on the map of pH. Their acidity is the result of an interrelationship between soil, climate and vegetation. However, afforestation, particularly with coniferous species, appears to lower the pH of the underlying soil. There is a trend in agricultural soils towards lower pH under a moister climate.     

The effects of habitat resolution on models of avian diversity and distributions: a comparison of two land-cover classifications

Quantifying patterns is a key element of landscape analysis. One aspect of this quantification of particular importance to landscape ecologists is the classification of continuous variables to produce categorical variables such as land-cover type or elevation stratum. Although landscape ecologists are fully aware of the importance of spatial resolution in ecological investigations, the potential importance of the resolution of classifications has received little attention. Here we demonstrate the effects of using two different land-cover classifications to predict avian species richness and the occurrences of six individual species across the conterminous United States. We compared models built with a data set based on 14 coarsely resolved land-cover variables to models built with a data set based on 160 finely resolved land-cover variables. In general, comparable models built with the two data sets fit the data to similar degrees, but often produced strikingly different predictions in various parts of the country. By comparing the predictions made by pairs of models, we determined in which regions of the US predictions were most sensitive to differences in land-cover classification. In general, these sensitive areas were different for four of the individual species and for predictions of species richness, indicating that alternate classifications will have different effects in the analyses of different ecological phenomena and that these effects will likely vary geographically. Our results lead us to emphasize the importance of the resolution to which continuous variables are classified in the design of ecological studies.This revised version was published online in May 2005 with corrections to the Cover Date.     

Exploring subtle land use and land cover changes: a framework for future landscape studies

Land cover and land use changes can have a wide variety of ecological effects, including significant impacts on soils and water quality. In rural areas, even subtle changes in farming practices can affect landscape features and functions, and consequently the environment. Fine-scale analyses have to be performed to better understand the land cover change processes. At the same time, models of land cover change have to be developed in order to anticipate where changes are more likely to occur next. Such predictive information is essential to propose and implement sustainable and efficient environmental policies. Future landscape studies can provide a framework to forecast how land use and land cover changes is likely to react differently to subtle changes. This paper proposes a four step framework to forecast landscape futures at fine scales by coupling scenarios and landscape modelling approaches. This methodology has been tested on two contrasting agricultural landscapes located in the United States and France, to identify possible landscape changes based on forecasting and backcasting agriculture intensification scenarios. Both examples demonstrate that relatively subtle land cover and land use changes can have a large impact on future landscapes. Results highlight how such subtle changes have to be considered in term of quantity, location, and frequency of land use and land cover to appropriately assess environmental impacts on water pollution (France) and soil erosion (US). The results highlight opportunities for improvements in landscape modelling.