Use of native mosses as biomonitors of heavy metals and nitrogen deposition in the surroundings of two steel works

A biomonitoring survey using the moss species Hypnum cupressiforme Hedw. was conducted in the surroundings of two steel plants located in the North of Spain. Levels of V, Cr, Ni, Cu, Zn, As, Cd, Hg, Pb and N were determined. Very high concentrations in the areas of study were detected when compared to nearby unaffected regions. Similar trends were observed for all the elements in the differently orientated transects, showing an appreciable influence of the NW prevailing winds of the region in the dispersion of pollutants, as well as a clear decreasing gradient in the concentrations of metals in mosses within a distance of 1500 meters from the facilities. A differentiation between the elements emitted by the chimney as result of the industrial activity (V, Cr, Ni, Cu and As) and those with a high presence in steel slag deposits (Zn, Cd, Hg and Pb) was observed. The range of contamination was also established by means of the Contamination Factor, indicating a category 4 out of 6 categories, which shows the high levels reported in the areas of study. A different dynamic was registered for nitrogen regarding the rest of the heavy metals analysed except for Hg, probably due to the elevated volatility and mobility of both elements, as well as their high persistence in the atmosphere.     

Perceptual deformation induced by visual motion

The perceived position of a moving object can be misleading because the object has advanced while its previous retinal image has been transmitted through the visual stream, leading to a mismatch between actual location and its neural representation. It has been suggested that the human visual system compensates for neural processing delays to retrieve instantaneous position. However, such a mechanism would require a precise measure of the actual delay in order to provide a reliable position estimate. A novel illusory deformation of moving contours demonstrates that humans misjudge the spatial relationship between parts of coherently moving targets, and therefore do not perfectly account for neural delays. The size of this deformation increases with growing speed. In some subjects this illusion can be reversed by varying the luminance of individual dots; a manipulation that affects the neural delays. Our experiments agree with other evidence that the capacity of the visual system to compensate for processing delays is limited.     

How To Tell Circles from Ellipses: Perceiving the Regularity of Simple Shapes

 Human observers achieve a surprising precision in many visual judgements, such as estimating relative position, colinearity and the regularity of shape. We measured the sensitivity in detecting shape deformations by presenting a square simultaneously with a rectangle of variable aspect ratio, or a circle with an ellipsoid. Weber fractions approach 3–5% and improve to approximately 1% when subjects are asked to tell which of the two objects was 'oriented more vertically′, instead of identifying the square or circle. Contour position can be judged with a precision of 10–20 arc s, clearly in the hyperacuity range and also beyond the thresholds known for detecting differences in the curvature of comparable line segments. Our results suggest that detecting deformation in rectangles seems to rely on aspect ratio, whereas performance is improved for ellipsoids by a high sensitivity for changes in local curvature. Received: 21 January 1999 / Accepted in revised form: 16 June 1999     

The development and application of remote sensing to monitor sand dune habitats

Sand dunes are complex systems that contain several habitats, often as mosaics or transitions between types. Several of these habitats are afforded protection under European Legislation and in the UK nationally within Special Areas of Conservation (SAC) and Sites of Special Scientific Interest (SSSI). Natural England has a statutory duty to report to Europe on the conservation status and condition of sand dunes; and is required to report to the UK Government on designated sites. To achieve this we have sought ways of capturing, analysing and interpreting data on the extent and location of sand dune habitats. This requires an ability to be able to obtain data over large areas of coastline in an efficient way. Natural England and Environment Agency Geomatics have worked collaboratively for over 16 years, sharing data and ecological knowledge. In 2012 work started to evaluate the use of remote sensing to map UK BAP and Annex I sand dune habitats. A methodology has now been developed and tested to map sand dune habitats. The key objective was to provide an operational tool that will help to map these habitats and understand change on sites around England. This has been achieved through analysis of LIDAR and Compact Airborne Spectrographic Imager (CASI) data using Object Orientated Image Analysis. Quality Control (QC) and accuracy assessments have shown this approach to be successful and 11 sites have been mapped to date. These techniques are providing a new approach to monitoring change in coastal vegetation communities and informing management of protected sites.