Hasse Diagram Technique Can Further Improve the Interpretation of Results in Multielemental Large-Scale Biomonitoring Studies of Atmospheric Metal Pollution

Abstract

Lichens and mosses have extensively been used in multielemental large-scale biomonitoring studies of atmospheric metal pollution. Despite its high importance in the assessment of cumulative risk and the communication with risk managers, the presentation and interpretation of biomonitoring results have only been partially the center of interest for a standardized methodology and for the harmonization of the techniques. Here we attempt to expand and improve the up-to-date formal presentation of biomonitoring results, combining the Hasse diagram technique with GIS techniques. The implementation using real data has demonstrated that such an expansion and improvement, in the direction of cumulative risk assessment and management, is feasible and it is suggested for incorporation in biomonitoring studies. Biomonitors and BiomonitoringLichens and mosses may be considered as the most commonly used organisms in biomonitoring studies of metal pollution in the atmospheric environment (Kularatne and Freitas 2013;Ares et al. 2012).Lichens are by definition symbiotic organisms, usually composed of a fungal partner, the mycobiont, and one or more photosynthetic partners, the photobiont, which is most often either a green alga or cyanobacterium (Nash 2008), while mosses are photosynthetic non-vascular and non-woody plants grouped in the

Use of the lichen Xanthoria mandschurica in monitoring atmospheric elemental deposition in the Taihang Mountains, Hebei, China

“…For the sake of simplicity and brevity, we mapped spatial patterns at cluster scale by using a combination of the Hasse diagram technique (HDT) and GIS techniques described by Pirintsos et al . 14 . The sampling sites were ranked based on the raw concentrations and EF SR s using HDT in order to present partial order relations 14 .…”

“… 14 . The sampling sites were ranked based on the raw concentrations and EF SR s using HDT in order to present partial order relations 14 . The outputs of HDT were subjected to Kriging interpolation and mapped to visualize spatial patterns.…”

“…Other maps ( Figs 3 and 4 ) were produced using a combination of HDT and GIS techniques to elucidate spatial patterns as described by Pirintsos et al . 14 . HDT was conducted separately on the seven clusters of lichen elements, in terms of raw concentration and EF SR , to rank the sampling sites, using the software Dart 2.0.5 (Talete srl 2007.…”

New Interpretative Scales for Lichen Bioaccumulation Data: The Italian Proposal

“…Another approach to the interpretation of biomonitoring data from native lichens is the use of interpretative scales [16] based on thresholds identifying classes of increasing element concentrations, and obtained by the meta-analysis of a large set of bioaccumulation data for epiphytic lichens at the national level [17]. The so-called "naturality/alteration scales", extensively applied until now (e.g., [18][19][20][21][22][23]), were originally proposed by Nimis and Bargagli and consist of seven classes of element concentrations built up on hundreds of data points collected in Italy between the 1980s and the 1990s [16]. Source data referred to 17 elements with a minimum of 100 records each, obtained from at least three biomonitoring surveys carried out in areas characterized by different pollution levels and geomorphology [16].…”