Data comparison.

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Presentation transcript:

Data comparison

If we want to estimate the alteration entity, accumulation data can basically be used following three different approaches: comparison with the minimum value measured in the survey area; use of an “interpretative scale”; comparison with background values. All three methods has advantages and drawbacks, each showing particular aspects of the phenomenon under study.

Comparison with the minimum value measured in the survey area Advantages: all those factors that may influence bioaccumulation are homogeneous: lichen species,tree species, measuring instruments, analytical procedure. It underlines possible influences deriving from climatic or pedological features of the survey area. It highlights well local patterns. Drawbacks: it underestimates uniform contamination phenomena extended on the whole survey area; It does not allow to estimate the entity of the contamination.

Mercury (Hg) Copper (Cu) From: Tretiach & Baruffo, 2001

Comparison with background values Background values are calculated as the average value of the lowest contents found in a high number of methodologically similar studies carried out in a single country (e.g. Italy) or geographical area (e.g. Antarctica). Advantages: uniform contamination phenomena extended to the whole survey area are recognized. This method allows the estimation of a deviation from “natural conditions”.

Comparison with background values Drawbacks: Studies specifically devoted to the collection of data in pristine or remote regions are very rare. It cannot be excluded that “pristine” areas of such a heavy anthropized country as is Italy, do not suffer long-distance pollution. Different background values should be estimated for lithological different areas, e.g. distinguishing between calcareous and siliceous regions. This information is totally lacking.

Linee-guida per il bioaccumulo Nimis & Bargagli (1999) 1998 Workshop “Biomonitoraggio della qualità dell’aria sul territorio nazionale”

The “interpretative scale” Nimis & Bargagli (1999) proposed an “interpretative scale” based on the analysis of hundreds of measurements carried out on in Italy using epiphytic foliose lichens, in survey areas with different climatic conditions, with different types of air pollution (intensity and sources)

there were at least 100 data collected in Percentile distribution values were calculated for each element for which there were at least 100 data collected in at least three distant areas of the country. An ordinary scale of 7 grades was built up on the basis of percentile classes of different width. The method suggests colours and definitions for each grade that can be used in graphic display and for the interpretation of the results. I percentili sono dei valori che permettono di dividere un gruppo di dati ordinati in cento parti, ognuna delle quali comprende l’1% dei dati. Esempio: avendo un set di cento dati ordinati in ordine crescente, il 20° percentile è quel valore che divide il 20% dei dati dal restante, cioè i primi venti dagli ultimi ottanta. I comuni software di calcolo comprendono formule e opzioni che permettono di ricavarli automaticamente.

Interpretation scale according to Nimis & Bargagli (1999) (modif. ) Interpretation scale according to Nimis & Bargagli (1999) (modif.). Values in µg g-1 dry weight. The idea was that the data set of each element had to be implemented year after year, as new studies were added, increasing the total number of data at disposal for the analysis

How the scale is built up Chromium Percentile class ppm N. collection sites in Italy whose samples have that specific concentration value n=654 ? 20° 75° 95° 50° 90° 98°

Three „mortal sins“:  Originally, no distinction was made among lichen species used.  The second sin was that the analytical procedures were mostly based on the “partial digestion” technique.  The last one that the data set with all the references was never published, i.e. nobody could control the data used in this statistical analysis.

Due scuole di pensiero: Usare scale basate su singole specie Usare una scala congiunta, basata su un alto numero di misure riferite a diverse specie oppure Usare scale basate su singole specie