Searching for lichen indicator species: the application of self-organizing maps in air quality assessment—a case study from Balkan area (Serbia)

ENVIRONMENTAL MONITORING AND ASSESSMENT(2020)

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Abstract
The subject of this paper is the possibility of using self-organizing map (SOM) in the biomonitoring studies. We used lichens as biomonitors to indicate different degrees of air quality. This research included all of 88 lichen species that was collected at 75 investigated points. These lichen species showed the different responses to air pollution. The air quality was assessed by IAP (index of atmospheric pollution) values. The IAP values were calculated for all of investigated points on the territory of four natural and one urban ecosystem. Calculated IAP values were in range of 10 to 75. On the basis of the lichen data and IAP values, we have employed SOM analysis that distinguished three clusters (A, B, and C). It presented lichen indicator species for each cluster: 16 species for cluster A, 18 species for cluster B, and two species for cluster C. This paper presents a useful method to find indicator species.
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Key words
Bioindication,Mapping,Zonification,SOM analysis,Clusters
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