Lichen mobile app

A mobile app using lichens to assess atmospheric nitrogen pollution effects has been developed by the Centre for Ecology & Hydrology (CEH).  The web-app is based on a field guide  produced in collaboration with Natural History Museum, The University of Nottingham, SNIFFER, JNCC, SNH, SEPA and NIEA, and published by the Field Studies Council. 

Recent research on UK oak and birch trees identified a set of ‘indicator’ lichens (sensitive and tolerant) with clear responses to increasing concentrations of atmospheric nitrogen pollutants. By identifying the presence or absence of nitrogen sensitive and non-sensitive lichens on tree trunks and branches you can get an estimate of how polluted your area is. Emphasis has been placed on the use of indicator lichens that do not require identification at the microscopic level and that are least likely to be confused with other species. The app includes some simple elements:

• Lichen identification key guide for nitrogen sensitive and tolerant species.
• Simple Recording system for surveying lichens on tree trunks and branches (only five trunks and five branches required).
• Field guide with instructions on carrying out the survey.
• Auto-calculated and robust method to determine nitrogen pollution levels using a standardised nitrogen air quality index (NAQI).
• Informs the public of their local nitrogen air quality based on four pollutant zones - 'Clean', 'At risk', 'Nitrogen Polluted’ or 'Very Nitrogen Polluted'.

Data collected will be deposited into the Biological Record Centre’s data warehouse linked to the iRecord system where it is accessible to you as the recorder, to an expert community of verifiers and other users of iRecord. Results will be available and mapped online with coloured map-markers representing the four pollutant zones.

The online field guide and user manual (pdf) can also be downloaded at the Lichen field manual home page for users wishing to do the survey without the use of a mobile device (via pencil and paper). Your results can then be inputted manually into the online web form and sent to the data warehouse.