Is the diversity of epiphytic lichens a reliable indicator of air pollution? A case study from Italy

This work provided additional information for a better interpretation of lichen diversity values in biomonitoring studies of air pollution. The effects of 12 predictive variables were estimated for the Genova province (NW Italy) by means of a non-parametric model. The diversity of epiphytic lichens was strictly correlated with mean annual rainfall and mean annual temperature. Different variables were found to affect the lichen diversity in urban vs. forested areas. In urban areas, air pollutants, mainly SO2, are still the main limiting factor, even if under ameliorating conditions this relationship becomes less significant. In forested areas, harvesting and forest fires showed a predominant effect, suggesting the need to develop a more defined sampling protocol to estimate atmospheric pollution in such ecosystems.     

Phosphate Analysis of Marine Sediments

Phosphate chemistry at the sediment-water interface could play a key role in the periodic eutrophication events characteristic of a N-W Adriatic coastal area. In order to establish a general knowledge of phosphate speciation in the sediments, we chose the sequential extraction procedure which gave most reproducible results as an analytical method. Comparison of data from the sequential procedure with that obtained with different methods using a single extraction step, indicates some inconsistencies due to the effects of chemical reagents on the sedimentary mineral composition.     

Reliability of different sampling densities for estimating and mapping lichen diversity in biomonitoring studies

Sampling requirements related to lichen biomonitoring include optimal sampling density for obtaining precise and unbiased estimates of population parameters and maps of known reliability. Two available datasets on a sub-national scale in Italy were used to determine a cost-effective sampling density to be adopted in medium-to-large-scale biomonitoring studies. As expected, the relative error in the mean Lichen Biodiversity (Italian acronym: BL) values and the error associated with the interpolation of BL values for (unmeasured) grid cells increased as the sampling density decreased. However, the increase in size of the error was not linear and even a considerable reduction (up to 50%) in the original sampling effort led to a far smaller increase in errors in the mean estimates (<6%) and in mapping (<18%) as compared with the original sampling densities. A reduction in the sampling effort can result in considerable savings of resources, which can then be used for a more detailed investigation of potentially problematic areas. It is, however, necessary to decide the acceptable level of precision at the design stage of the investigation, so as to select the proper sampling density.     

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

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.     

Evaluation of data quality in lichen biomonitoring studies: the Italian experience

A total of 65 operators involved in lichen mapping studies in central and northwestern Italy underwent quality control tests during five lichen biomonitoring workshops organized between 1999and 2000. The results showed that 75% quantitative accuracy and90% quantitative precision can be regarded as satisfactory levels for lichen biodiversity data; 65% proved to be sufficientfor accuracy of taxonomic identification in the field. Average correct assignment of the interpretative naturality/alteration class was only 48.7%. The results indicated the need for taxonomic training.     

Adaptive cluster double sampling with post stratification with application to an epiphytic lichen community

The implementation of an adaptive cluster sampling design often becomes logistically challenging because variation in the final sampling effort introduces uncertainty in survey planning. To overcome this drawback, an inexpensive and easy to measure auxiliary variable could be used in a two-phase survey strategy, called adaptive cluster double sampling (Félix-Medina and Thompson in Biometrika 91:877–891, 2004). In this paper, a two-phase sampling strategy is proposed which combines the idea of adaptive cluster double sampling with the principle of post-stratification. In the first-phase an adaptive cluster sample is selected by means of an inexpensive auxiliary variable. Networks from the first phase sampling are then post-stratified according to their size. In the second-phase, the network structure is used to select a subsample of units by means of stratified random sampling. The proposed sampling strategy employs stratification without requiring an a priori delineation of the strata. Indeed, the strata sizes are estimated in the course of the two-phase sampling process. Therefore, it is suitable for situations where stratification is suspected to be efficient but strata cannot be easily delineated in advance. In this framework, a new type of estimator for the population mean which mimics the stratified sampling mean estimator and an estimator of the sampling variance are proposed. The results of a simulation study confirm, as expected, that the use of post-stratification leads to gain in precision for the estimator. The proposed sampling strategy is applied for targeting an epiphytic lichen community Lobarion pulmonariae in a forest area of the Northern Apennines (N-Italy), characterized by several species of conservation concern.     

Phytoremediation of Soil Polluted by Nickel Using Agricultural Crops

Soil pollution due to heavy metals is widespread; on the world scale, it involves about 235 million hectares. The objectives of this research were to establish the uptake efficiency of nickel by some agricultural crops. In addition, we wanted to establish also in which part of plants the metal is stored for an eventual use of biomass or for recycling the metal. The experiments included seven herbaceous crops such as: barley (Hordeum vulgaris), cabbage (Brassica juncea), spinach (Spinacea oleracea), sorghum (Sorgum vulgare), bean (Phaseolus vulgaris), tomato (Solanum lycopersicum), and ricinus (Ricinus communis). We used three levels of treatment (150, 300, and 600 ppm) and one control. At the end of the biological cycle of the crops, the different parts of plants, i.e., roots, stems, leaves, fruits, or seeds, were separately collected, oven dried, weighed, milled, and separately analysed. The leaves and stems of spinach showed a very good nickel storage capacity. The ricinus too proved to be a very good nickel storer. The ability of spinach and ricinus to store nickel was observed also in the leaves of cabbage, even if with a lower storage capacity. The bean, barley, and tomato, in decreasing order of uptake and storage capacity, showed a high concentration of nickel in leaves and stems, whereas the sorghum evidenced a lesser capacity to uptake and store nickel in leaves and stems. The bean was the most efficient in storing nickel in fruits or grains. Tomato, sorghum, and barley have shown a storage capacity notably less than bean. The bean appeared to be the most efficient in accumulating nickel in the roots, followed in decreasing order by sorghum, ricinus, and tomato. With regard to the removal of nickel, spinach was the most efficient as it contains the highest level of this metal per gram of dry matter. The ricinus, cabbage, bean, sorghum, barley, and tomato evidenced a progressively decreasing efficiency in the removal of nickel.     

The response of epiphytic lichens to air pollution and subsets of ecological predictors: a case study from the Italian Prealps

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.     

Effects of atmospheric pollution on lichen biodiversity (LB) in a Mediterranean region (Liguria, northwest Italy)

The effects of air pollution on lichen biodiversity (LB) were monitored in Liguria (northwest Italy). A systematic sampling strategy was adopted in order to avoid the influence of spatial autocorrelation on the results. An eight LB class scale permitted to point out the levels of naturality/alteration in the region. The comparison of these results with the ones obtained by mean of physico-chemical methodologies shows a good accordance. The results of this study suggest the possibility of designing an integrated monitoring network, in which biological monitoring will allow to estimate the level of alteration in remote areas, which account for most of this region and which are currently not covered by measurements with automatic systems.