Lichens have been widely used as biomonitoring of atmospheric pollution, because these organisms respond to phytotoxic gases (especially SO2 and NOx) at cellular, individual and community level. Nevertheless, due to the biological and ecological variability of the organisms, scientists often find difficult to discern the effects of pollution against a natural background noise. On the other hand, statistically supported responses are needed if we aim to include these techniques in decisional processes of environmental management. In this chapter we try to investigate this complex trade-off, by focusing the attention on bioindication techniques, based on the observation of a decreased richness of lichen communities, related to increasing concentration of atmospheric pollutants. In particular we present worked examples of biomonitoring applications in heterogeneous environments, to provide an overview of main sampling, analytical and statistical procedures, which can lead scientists and stakeholders to a better knowledge of the relationship between lichen diversity and air pollution. We take into account three main factors of variability for lichen communities across spatial and temporal scales. In the first case, we investigate the different responses of lichens to atmospheric pollutants in relation to macroclimatic predictors. Because of close dependence on the atmosphere for their metabolic processes, lichens are strongly influenced by climate-related variables (e.g. rainfall and temperature). It was shown how, under the same level of air pollution, lichen diversity is higher in areas with higher rainfall. We present results from dry vs. humid bioclimatic areas in Italy and we discuss how synergistic and antagonistic relations among pollutants, lichen and climate may significantly vary, together with the predictive power of biomonitoring methods. Modern approach to environmental assessments includes an evaluation of the pollution impact not only on human health, but also on natural heritage. Hence, lichen biomonitoring was used to detect the effects of gaseous pollutants on natural ecosystems. In the second example, we show that, in the framework of lichen biomonitoring in natural forests, habitat-related variables may play a major role on lichen diversity and more caution should be taken when interpreting these data in terms of direct effects of pollution. At a more detailed spatial scale, the variability of lichen diversity can be very high and consequently the level of uncertainty in the interpretation of data may arise considerably. This should be taken into account when higher scale surveys are planned, by considering an adequate sampling intensity at within-site scale. In the third working example we discuss this issue, showing data from intensive experiments and comparing the variability unrelated to atmospheric pollution at local scale in natural environments with that observed at higher scale in anthropized ones. © 2010 Nova Science Publishers, Inc.

Lichen biomonitoring of air pollution: Issues for applications in complex environments

BRUNIALTI, GIORGIO;RIZZI, GUIDO;GIORDANI, PAOLO
2011

Abstract

Lichens have been widely used as biomonitoring of atmospheric pollution, because these organisms respond to phytotoxic gases (especially SO2 and NOx) at cellular, individual and community level. Nevertheless, due to the biological and ecological variability of the organisms, scientists often find difficult to discern the effects of pollution against a natural background noise. On the other hand, statistically supported responses are needed if we aim to include these techniques in decisional processes of environmental management. In this chapter we try to investigate this complex trade-off, by focusing the attention on bioindication techniques, based on the observation of a decreased richness of lichen communities, related to increasing concentration of atmospheric pollutants. In particular we present worked examples of biomonitoring applications in heterogeneous environments, to provide an overview of main sampling, analytical and statistical procedures, which can lead scientists and stakeholders to a better knowledge of the relationship between lichen diversity and air pollution. We take into account three main factors of variability for lichen communities across spatial and temporal scales. In the first case, we investigate the different responses of lichens to atmospheric pollutants in relation to macroclimatic predictors. Because of close dependence on the atmosphere for their metabolic processes, lichens are strongly influenced by climate-related variables (e.g. rainfall and temperature). It was shown how, under the same level of air pollution, lichen diversity is higher in areas with higher rainfall. We present results from dry vs. humid bioclimatic areas in Italy and we discuss how synergistic and antagonistic relations among pollutants, lichen and climate may significantly vary, together with the predictive power of biomonitoring methods. Modern approach to environmental assessments includes an evaluation of the pollution impact not only on human health, but also on natural heritage. Hence, lichen biomonitoring was used to detect the effects of gaseous pollutants on natural ecosystems. In the second example, we show that, in the framework of lichen biomonitoring in natural forests, habitat-related variables may play a major role on lichen diversity and more caution should be taken when interpreting these data in terms of direct effects of pollution. At a more detailed spatial scale, the variability of lichen diversity can be very high and consequently the level of uncertainty in the interpretation of data may arise considerably. This should be taken into account when higher scale surveys are planned, by considering an adequate sampling intensity at within-site scale. In the third working example we discuss this issue, showing data from intensive experiments and comparing the variability unrelated to atmospheric pollution at local scale in natural environments with that observed at higher scale in anthropized ones. © 2010 Nova Science Publishers, Inc.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/874488
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