Biomonitoring by means of the supersensitive cultivar Nicotiana tabacum Bel-W3 is frequently used to obtain information on ozone effects on plants and estimates of ozone exposure. However, most of biomonitoring surveys do not account for other environmental variables (predictors in a statistical model) and their inherent multicollinearity with ozone. We tested the relative role of different predictors (fixed: time and site; random: ozone, temperature and humidity) on height growth and on the development of visible foliar symptoms of N. tabacum Bel-W3 plants. To do this, we investigated a relatively small area (256 km2), used a random design at every stage of the survey, controlled watering and protected plants from direct solar radiation and wind. QA/QC procedures were adopted at every stage of the investigation. Linear correlation shows that Leaf Injury Index (LII) and height increment (H.I.) positively related to ozone concentration, elevation and temperature, and negatively to relative humidity. All the predictors correlate to each other. However, relationships between response and ozone vary with the site and the monitoring week. The effect of the random factor “ozone” in combination with fixed factors “site” and “time” on the response variables was therefore formally investigated using the ANCOVA model. Besides ozone, the interactions “ozone × site” and “ozone × time” resulted always significant (0.001 < P < 0.05). While the factor “time” emphasize the inherent development of injury and growth through time, the interaction “ozone × site” pointed out the importance of local conditions. When watering, solar radiation, wind and plant characteristics were controlled, the remaining site-specific covariates of interest were temperature (T) and humidity (RH). When T and RH were accounted for by means of partial correlation analysis, no significant relationship was found between ozone and LII. On the other side, O3 and RH resulted significant for both absolute and relative height increment. In short, LII seemed to be not solely dependent on ozone, T and RH, but showed to integrate their combined effect. On the other side, H.I. seemed to be favoured by high RH and T, and depressed by high ozone. Based on the above results, we recommend caution when handling bioindicator data: if the purpose is to infer ozone concentrations by leaf injury data, results may be affected by a serious bias, as the frequently reported correlations may be partly an artefact due to co-variation between predictors.
Cristofolini, F.; Cristofori, A.; Gottardini, E.; Maccherini, S.; Ferretti, M. (2011). Constraints in the identification and interpretation of ozone as a significant predictor of effects on the supersensitive indicator Nicotiana tabacum Bel-W3 in biomonitoring studies. ECOLOGICAL INDICATORS, 11 (5): 1065-1073. doi: 10.1016/j.ecolind.2010.12.003 handle: http://hdl.handle.net/10449/20002
Constraints in the identification and interpretation of ozone as a significant predictor of effects on the supersensitive indicator Nicotiana tabacum Bel-W3 in biomonitoring studies
Cristofolini, Fabiana;Cristofori, Antonella;Gottardini, Elena;
2011-01-01
Abstract
Biomonitoring by means of the supersensitive cultivar Nicotiana tabacum Bel-W3 is frequently used to obtain information on ozone effects on plants and estimates of ozone exposure. However, most of biomonitoring surveys do not account for other environmental variables (predictors in a statistical model) and their inherent multicollinearity with ozone. We tested the relative role of different predictors (fixed: time and site; random: ozone, temperature and humidity) on height growth and on the development of visible foliar symptoms of N. tabacum Bel-W3 plants. To do this, we investigated a relatively small area (256 km2), used a random design at every stage of the survey, controlled watering and protected plants from direct solar radiation and wind. QA/QC procedures were adopted at every stage of the investigation. Linear correlation shows that Leaf Injury Index (LII) and height increment (H.I.) positively related to ozone concentration, elevation and temperature, and negatively to relative humidity. All the predictors correlate to each other. However, relationships between response and ozone vary with the site and the monitoring week. The effect of the random factor “ozone” in combination with fixed factors “site” and “time” on the response variables was therefore formally investigated using the ANCOVA model. Besides ozone, the interactions “ozone × site” and “ozone × time” resulted always significant (0.001 < P < 0.05). While the factor “time” emphasize the inherent development of injury and growth through time, the interaction “ozone × site” pointed out the importance of local conditions. When watering, solar radiation, wind and plant characteristics were controlled, the remaining site-specific covariates of interest were temperature (T) and humidity (RH). When T and RH were accounted for by means of partial correlation analysis, no significant relationship was found between ozone and LII. On the other side, O3 and RH resulted significant for both absolute and relative height increment. In short, LII seemed to be not solely dependent on ozone, T and RH, but showed to integrate their combined effect. On the other side, H.I. seemed to be favoured by high RH and T, and depressed by high ozone. Based on the above results, we recommend caution when handling bioindicator data: if the purpose is to infer ozone concentrations by leaf injury data, results may be affected by a serious bias, as the frequently reported correlations may be partly an artefact due to co-variation between predictors.
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