(Table 3) Collembola species density and diversity in control and OTC plots near Abisco Research Station

Ecosystems at high northern latitudes are subject to strong climate change. Soil processes, such as carbon and nutrient cycles, which determine the functioning of these ecosystems, are controlled by soil fauna. Thus assessing the responses of soil fauna communities to environmental change will improve the predictability of the climate change impacts on ecosystem functioning. For this purpose, trait assessment is a promising method compared to the traditional taxonomic approach, but it has not been applied earlier. In this study the response of a sub-arctic soil Collembola community to long-term (16 years) climate manipulation by open top chambers was assessed. The drought-susceptible Collembola community responded strongly to the climate manipulation, which substantially reduced soil moisture and slightly increased soil temperature. The total density of Collembola decreased by 51% and the average number of species was reduced from 14 to 12. Although community assessment showed species-specific responses, taxonomically based community indices, species diversity and evenness, were not affected. However, morphological and ecological trait assessments were more sensitive in revealing community responses. Drought-tolerant, larger-sized, epiedaphic species survived better under the climate manipulation than their counterparts, the meso-hydrophilic, smaller-sized and euedaphic species. Moreover it also explained the significant responses shown by four taxa. This study shows that trait analysis can both reveal responses in a soil fauna community to climate change and improve the understanding of the mechanisms behind them.

GPS raw data (control points and ground control points) from the Liguria Region, Borghetto Santo Spirito, Italy

Monitoring the impact of sea storms on coastal areas is fundamental to study beach evolution and the vulnerability of low-lying coasts to erosion and flooding. Modelling wave runup on a beach is possible, but it requires accurate topographic data and model tuning, that can be done comparing observed and modeled runup. In this study we collected aerial photos using an Unmanned Aerial Vehicle after two different swells on the same study area. We merged the point cloud obtained with photogrammetry with multibeam data, in order to obtain a complete beach topography. Then, on each set of rectified and georeferenced UAV orthophotos, we identified the maximum wave runup for both events recognizing the wet area left by the waves. We then used our topography and numerical models to simulate the wave runup and compare the model results to observed values during the two events. Our results highlight the potential of the methodology presented, which integrates UAV platforms, photogrammetry and Geographic Information Systems to provide faster and cheaper information on beach topography and geomorphology compared with traditional techniques without losing in accuracy. We use the results obtained from this technique as a topographic base for a model that calculates runup for the two swells. The observed and modeled runups are consistent, and open new directions for future research.