The VDI approach is a standardized German method that was devised to assess changes in lichen communities over wide geographical areas in order to assess the influence of air pollution in Central Europe. The method is based on the frequency of occurrence of selected widespread lichen species within a unit area on selected tree trunks.
The VDI method is based on establishing a grid over the area to be surveyed, whose units would vary according to the availability of suitable tree species and the size of the area to be surveyed. 3-6 trees conforming to established criteria are selected in each grid square for recording lichens within a grid of 0.1 m x 0.1 m units measuring 0.2 m x 0.5 m, placed at 1.50 m on the tree trunk where lichens are most frequent. The frequency of selected species is assessed and the air quality value (LGW) expressed as the average of the total sum of frequencies for each grid sample.
This highly selective approach has been widely used for producing maps of polluted zones around point sources and in urban areas (VDI, 1995). It has since been replaced by the European method in order to allow further analysis of whole data sets and to detect changes in the lichen flora.
This method has been successfully applied to assess the impacts of SO2 over large areas where industrial and domestic burning of fossil fuels has occurred in Germany and a similar method of using an Index of Atmospheric Purity has been applied successfully in Italy, where a weighting for toxiphoby was applied (Kirschbaum, 1995,1996, 1998).
Loppi et al. (1996) used this method in central Italy on lichen communities of Quercus species in agricultural and protected areas where bark pH and total nitrogen content were determined. They showed that the distribution of nitrophytes (identified according to Wirth and van Dobben) did not correspond to bark pH or %nitrogen. Loppi et al. (2000) investigated the distribution of nitrophytes in the vicinity of limestone and sandstone quarries where results showed a correlation with dust that was independent of its base status.
Testing of this method at in the vicinity of a poultry farm in Scotland (Pitcairn et al. 2003) this report showed that this method provided very similar results to the European Lichen Diversity Values (LDV) system. An initial decrease with increasing NH3, was followed by an increase in Lichen diversity by both methods, as nitrophyte species replace acidophytes.
Suitability to indicate atmospheric concentrations:
Not well suited because of the complex relationships with atmospheric N concentrations.
Suitability to indicate atmospheric depositions:
Not well suited because of the complex relationships with atmospheric N deposition.
Suitability to indicate environmental impacts:
By definition changes in lichen biodiversity represent an impact of N. However, the method is not well suited to monitoring N impacts, as diversity is influenced by the presence of both nitrophyte and acidophyte species.
Sensitivity to other factors:
There are many changes that are occurring in urban areas following the fall in SO2 levels over the past two decades, and the data provided from frequency of selected species does not allow multivariate analysis to provide a basis for assessing ongoing environmental changes.
Lichen diversity on tree trunks represents the accumulated effect of pollution climate over the past few decades. Under conditions of improving air quality, it may take many years for recovery. Lichen diversity measurements on twigs represent changes over a shorter period.
Only applicable where sufficient number of trees fulfilling sampling criteria.
Expertise in field:
Requires staff trained to recognise a few selected lichen species.
Expertise in laboratory:
Trained personnel are not required as equation applied to quantified results.
Cost (per unit sample): £unknown
Cost Comment: Agency staff may be trained to conduct the basic level of identification necessary. Locating sites in the vicinity needs 1 day, and sampling of 10 trees per site needs 1.5 days. The total cost also needs to account for travel and data analysis time.