Airborne radiometric survey data and a DTM as covariates for regional scale mapping of soil organic carbon across Northern Ireland

Soil scientists require cost-effective methods to make accurate regional predictions of soil organic carbon (SOC) content. We assess the suitability of airborne radiometric data and digital elevation data as covariates to improve the precision of predictions of SOC from an intensive survey in Northern Ireland. Radiometric data (K band) and, to a lesser extent, altitude are shown to increase the precision of SOC predictions when they are included in linear mixed models of SOC variation. However the statistical distribution of SOC in Northern Ireland is bimodal and therefore unsuitable for geostatistical analysis unless the two peaks can be accounted for by the fixed effects in the linear mixed models. The upper peak in the distribution is due to areas of peat soils. This problem may be partly countered if soil maps are used to classify areas of Northern Ireland according to their expected SOC content and then different models are fitted to each of these classes. Here we divide the soil in Northern Ireland into three classes, namely mineral, organo-mineral and peat. This leads to a further increase in the precision of SOC predictions and the median square error is 2.2 %2. However a substantial number of our observations appear to be mis-classified and therefore the mean squared error in the predictions is larger (30.6 %2) since it is dominated by large errors due to mis-classification. Further improvement in SOC prediction may therefore be possible if better delineation between areas of large SOC (peat) and small SOC (non-peat) could be achieved

Soil quality assessment under emerging regulatory requirements

New and emerging policies that aim to set standards for protection and sustainable use of soil are likely to require identification of geographical risk/priority areas. Soil degradation can be seen as the change or disturbance in soil quality and it is therefore crucial that soil and soil quality are well understood to protect soils and to meet legislative requirements. To increase this understanding a review of the soil quality definition evaluated its development, with a formal scientific approach to assessment beginning in the 1970s, followed by a period of discussion and refinement. A number of reservations about soil quality assessment expressed in the literature are summarised. Taking concerns into account, a definition of soil quality incorporating soil's ability to meet multifunctional requirements, to provide ecosystem services, and the potential for soils to affect other environmental media is described. Assessment using this definition requires a large number of soil function dependent indicators that can be expensive, laborious, prone to error, and problematic in comparison. Findings demonstrate the need for a method that is not function dependent, but uses a number of cross-functional indicators instead. This method to systematically prioritise areas where detailed investigation is required, using a ranking based against a desired level of action, could be relatively quick, easy and cost effective. As such this has potential to fill in gaps and compliment existing monitoring programs and assist in development and implementation of current and future soil protection legislation