The variability of biological data is a main constraint affecting the quality and reliability of lichen biomonitoring surveys for estimation of the effects of atmospheric pollution. Although most epiphytic lichen bioindication surveys focus on between-site differences at the landscape level, associated with the large scale effects of atmospheric pollution, current protocols are based on multilevel sampling, thus adding further sources of variation and affecting the error budget. We test the hypothesis that assemblages of lichen communities vary at each spatial scale examined, in order to determine what scales should be included in future monitoring studies. We compared four sites in Italy, along gradients of atmospheric pollution and climate, to test the partitioning of the variance components of lichen diversity across spatial scales (from trunks to landscapes). Despite environmental heterogeneity, we observed comparable spatial variance. However, residuals often overcame between-plot variability, leading to biased estimation of atmospheric pollution effects.

Spatial scales of variation in lichens: Implications for sampling design in biomonitoring surveys

INCERTI, Guido;
2013-01-01

Abstract

The variability of biological data is a main constraint affecting the quality and reliability of lichen biomonitoring surveys for estimation of the effects of atmospheric pollution. Although most epiphytic lichen bioindication surveys focus on between-site differences at the landscape level, associated with the large scale effects of atmospheric pollution, current protocols are based on multilevel sampling, thus adding further sources of variation and affecting the error budget. We test the hypothesis that assemblages of lichen communities vary at each spatial scale examined, in order to determine what scales should be included in future monitoring studies. We compared four sites in Italy, along gradients of atmospheric pollution and climate, to test the partitioning of the variance components of lichen diversity across spatial scales (from trunks to landscapes). Despite environmental heterogeneity, we observed comparable spatial variance. However, residuals often overcame between-plot variability, leading to biased estimation of atmospheric pollution effects.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/1100515
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