The response of epiphytic lichens to air pollution and subsets of ecological predictors: a case study from the Italian Prealps. - Cristofolini, Fabiana; Giordani, Paolo; Gottardini, Elena; Modenesi, Paolo (Environmental pollution (Barking, Essex : 1987), 2008)
We investigated the response of epiphytic lichens to air pollution, against the background of other ecological predictors in a prealpine heterogeneous area, using Non-Parametric Multiplicative Regression (NPMR). The best NPMR model for total lichen diversity according to N environmental predictors at tree level has a cross R(2)=0.709. It includes 10 variables, belonging to three different subsets of factors: two pollution-related factors (distance in meters from the road and from the cement factory); four stand-related (habitat, heat index, LAI and elevation) and four substrate-related factors (inclination, circumference and texture and tree species). Considering separately the effects of each subset on lichen diversity, substrate- and stand-related factors produce good models with similar cross R(2) (0.490 and 0.500, respectively), whereas pollution-related factors produce a model with a lower cross R(2) (0.340). Hence, we provide information to investigate the applicability of lichen biomonitoring to complex heterogeneous areas where standardized protocols are not reliable.
Keywords: Ecological factors; Lichen diversity; NPMR; Standardized protocol; Toblino

The response of epiphytic lichens to air pollution and subsets of ecological predictors: a case study from the Italian Prealps. - Cristofolini, Fabiana; Giordani, Paolo; Gottardini, Elena; Modenesi, Paolo (Environmental pollution (Barking, Essex : 1987), 2008)
We investigated the response of epiphytic lichens to air pollution, against the background of other ecological predictors in a prealpine heterogeneous area, using Non-Parametric Multiplicative Regression (NPMR). The best NPMR model for total lichen diversity according to N environmental predictors at tree level has a cross R(2)=0.709. It includes 10 variables, belonging to three different subsets of factors: two pollution-related factors (distance in meters from the road and from the cement factory); four stand-related (habitat, heat index, LAI and elevation) and four substrate-related factors (inclination, circumference and texture and tree species). Considering separately the effects of each subset on lichen diversity, substrate- and stand-related factors produce good models with similar cross R(2) (0.490 and 0.500, respectively), whereas pollution-related factors produce a model with a lower cross R(2) (0.340). Hence, we provide information to investigate the applicability of lichen biomonitoring to complex heterogeneous areas where standardized protocols are not reliable.
The following values have no corresponding Zotero field: accession-num: 17689161
Keywords: Ecological factors; Lichen diversity; NPMR; Standardized protocol; Toblino