Seawater carbonate chemistry in Ischia, Italy, 2008

The atmospheric partial pressure of carbon dioxide (pCO2) will almost certainly be double that of pre-industrial levels by 2100 and will be considerably higher than at any time during the past few million years1. The oceans are a principal sink for anthropogenic CO2 where it is estimated to have caused a 30% increase in the concentration of H+ in ocean surface waters since the early 1900s and may lead to a drop in seawater pH of up to 0.5 units by 2100. Our understanding of how increased ocean acidity may affect marine ecosystems is at present very limited as almost all studies have been in vitro, short-term, rapid perturbation experiments on isolated elements of the ecosystem4, 5. Here we show the effects of acidification on benthic ecosystems at shallow coastal sites where volcanic CO2 vents lower the pH of the water column. Along gradients of normal pH (8.1-8.2) to lowered pH (mean 7.8-7.9, minimum 7.4-7.5), typical rocky shore communities with abundant calcareous organisms shifted to communities lacking scleractinian corals with significant reductions in sea urchin and coralline algal abundance. To our knowledge, this is the first ecosystem-scale validation of predictions that these important groups of organisms are susceptible to elevated amounts of pCO2. Sea-grass production was highest in an area at mean pH 7.6 (1,827 µatm pCO2) where coralline algal biomass was significantly reduced and gastropod shells were dissolving due to periods of carbonate sub-saturation. The species populating the vent sites comprise a suite of organisms that are resilient to naturally high concentrations of pCO2 and indicate that ocean acidification may benefit highly invasive non-native algal species. Our results provide the first in situ insights into how shallow water marine communities might change when susceptible organisms are removed owing to ocean acidification.

Alkenone-derived UK'37 data and sea surface temperatures (SST) of sediment cores from the Gulf of Taranto (Italy)

Auxiliary data include one file with alkenone-derived UK'37 data and sea surface temperatures (SST). On these data Figs. 7 and 8 of the manuscript are based. The SST are derived from UK'37 by using the transfer function: SST = 29.876 UK'37 - 1.334 of Conte et al. (2006). The data are against the ages (in A.D.) of samples derived from cores GT91-1 (39[deg]59'23"N, 17[deg]45'25"E), GT89-3 and GT90-3 (both 39[deg]45'43"N, 17[deg]53'55"E ). Also included are composite records for UK'37 and SST. For creating the composite records, GT-89-3 was taken as reference core. In the overlapping period the GT89-3 data seem in general lower than the GT91-1 data. To accommodate for this in the composite record, the average difference (0.0343 UK'37 units; equivalent to 1.023 [deg]C) was subtracted from the GT91-1 record. Hereafter, for each depth in the overlapping interval the respective values (UK'37 or SST) of GT89-3 and GT91-1 were averaged. We have also averaged with 16 additional alkenone measurements, from 1793 to 1851, performed in the GT90-3 core.

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.