A multidiversity approach to investigate the impact of mining exploitation on spider diversity in the abandoned mine district of Montevecchio-Ingurtosu (Sardinia, Italy).

The impact of mining activities on spider (Araneae) diversity and assemblages was studied in two abandoned mine sites in Sardinia (Italy), where mining activities started in the middle of the nineteenth century and closed down over a century later. Spider community composition was analysed in dumps, undisturbed forests and scrublands which represent the natural chronosequence following the abandonment of the mining district. The identification of spiders was performed at the lowest taxonomic level possible and differences in abundance, species richness (SR), and functional diversity (FD) were analysed. Nonmetric multidimensional scaling (NMDS) and a permutated multivariate analysis of variance (PERMANOVA) routine were conducted to evaluate the relationships of spider assemblages with land cover, and the indicator species analysis was performed to identify the typifying species. During the entire sampling period, 2312 spiders were captured, and approximately 80% of the total were identified at the species level (79 spider species belonging to 28 different families). No differences in abundance and SR were found, whereas FD, which showed the highest values in forests, significantly differed among sites. A distinct separation among assemblages and a significant effect of the land use on spider assemblages were found (PERMANOVA, R2 = 0.59, p < 0.001). Twelve species were selected as indicator species. Our results underlined the possibility to consider ground-dwelling spiders as a valuable target group for biomonitoring programmes supporting projects of near-natural restoration and/or technical reclamation of mining sites.

Combination of beehive matrices analysis and ant biodiversity to study heavy metal pollution impact in a post-mining area (Sardinia, Italy).

Mining activities represent a major source of environment contamination. The aim of this study was to evaluate the use of bees and ants as bioindicators to detect the heavy metal impact in post-mining areas. A biomonitoring programme involving a combination of honeybee hive matrices analysis and ant biodiversity survey was conducted over a 3-year period. The experimental design involved three monitoring stations where repeated sampling activities focused on chemical detection of cadmium (Cd), chrome (Cr) and lead (Pb) from different matrices, both from hosted beehives (foraging bees, honey and pollen) and from the surrounding environment (stream water and soil). At the same time, ant biodiversity (number and abundance of species) was determined through a monitoring programme based on the use of pitfall traps placed in different habitats inside each mining site. The heavy metal content detected in stream water from the control station was always below the analytical limit of quantification. In the case of soil, the content of Cd and Pb from the control was lower than that of mining sites. The mean heavy metal concentrations in beehive matrices from mining sites were mainly higher than the control, and as a result of regression and discriminant analysis, forager bee sampling was an efficient environmental pollution bioindicator. Ant collection and identification highlighted a wide species variety with differences among habitats mostly associated with vegetation features. A lower variability was observed in the polluted landfill characterised by lack of vegetation. Combined biomonitoring with forager bees and ants represents a reliable tool for heavy metal environmental impact studies.