Mollusc fauna associated with the Cystoseira algal associations in the Gulf of Trieste (Northern Adriatic Sea)

Mollusc assemblages associated with Cystoseira associations were sampled in the southern part of the Gulf of Trieste during the summers of 2008 and 2012. Samples were collected by SCUBA diving in the infralittoral belt (from 1 to 4 m depth). The surface within frames of 20 x 20 cm was scraped off with samples were collected by hand or with an air-lift sampler. Four erected algal species were found: Cystoseira barbata, C. compressa, C. corniculata and Halopithys incurva. A total of 69 species of molluscs were identified in those associations. Gastropoda were dominant, with the highest species richness and abundance, followed by Bivalvia and Polyplacophora. A large number of juveniles were found, proving the importance of Cystoseira associations for mollusc recruitment. Differences in composition, structure and abundance of mollusc assemblages were found for sites dominated by different algal species, and correspond to different morphology and degree of development of canopy-forming species. The present study confirms that the dominant algal species within Cystoseira associations strongly influence, although at different levels, abundance and distribution of mollusc assemblages in the Northern Adriatic Sea

Multiannual trend of micro-pollutants in sediments and benthic community response in a mediterranean lagoon (Sacca di Goro, Italy)

Long-term variations of ecological status in a Mediterranean coastal lagoon (Sacca di Goro, Northern Adriatic) were investigated, combining data on the concentration of surface sediment contaminants and on the structure of the macrobenthic community. The aim was to assess any amount of chemical contamination and check the response of the macrobenthic community to sediment contamination. Over the studied period, the sediments of the lagoon showed contamination by trace metals and organochlorine pesticides, with most of them exceeding the thresholds indicated by the Italian legislation in many samples. Contamination by polychlorinated dibenzodioxins and dibenzofurans (PCDD/Fs) and polycyclic aromatic hydrocarbons (PAHs) instead never exceeded the threshold. The ecological status based on the macrobenthic community, evaluated through biotic indices (AMBI and M-AMBI), fell below the Good/Moderate threshold in most samples. The results indicate a possible influence of toxic compounds in sediment on benthic organisms, but most of the variability shown by the macrobenthic community is probably due to other factors. The difficulty in establishing a cause/effect relationship was due to the co-occurrence and variability of various stressors (both natural and anthropogenic) and their interactions. The methods currently used for monitoring transitional waters thus seem insufficient to disentangle the effect of pollutants and other environmental variables on the benthos. Integrated approaches (e.g., bioaccumulation and toxicity tests) are thus needed for a more precise identification of the risk posed by a high concentration of pollutants in such environments

Sediment contamination by heavy metals and PAH in the Piombino Channel (Tyrrhenian Sea).

Sediment contamination is of major concern in areas affected by heavy maritime traffic. The spatial variation and contamination of 11 trace elements and 17 PAHs in surface sediments were studied along a 31 km transect along the seaway from the port of Piombino (Tuscany) to the port of Portoferraio (Elba Island) in the Northern Tyrrhenian Sea. Heavy metal contamination was detected at sites near Piombino (Ni, Pb, Hg, Cu and Zn) and at sites near Portoferraio (Pb, Zn, Hg, Cr and Cd). Each of the 35 sampled sites showed PAH contamination, with the highest concentrations at sites near Portoferraio. The most abundant isomers detected were 2- and 4-ring PAHs. PAH ratio analysis showed a prevalence of PAHs of pyrolytic origin. High values of PAHs and heavy metals were related to high sediment water content, TOC, silt, and clay content. Arsenic increased with increasing depth. The correlation between concentrations of metals and PAHs suggests common anthropogenic sources and is of concern for possible synergistic adverse effects on the biota

Recycling of multilayer packaging waste with switchable anionic surfactants

Switchable Anionic Surfactants (SAS) were used for delaminating flexible packaging waste composed of various plastic layers and aluminium, thereby promoting the recycling of such waste streams from a circular economy perspective. The delamination protocol was optimized on de-pulped food and beverage cartons containing low-density polyethylene (LDPE) and aluminium, varying the carboxylic acid and its counterion constituting the SAS (C8[sbnd]C18 carboxylic acids as the anionic part; inorganic bases and primary, secondary and tertiary amines as the cationic one) their molar ratio (carboxylic acid: base molar ratio from 1:1 to 1:3), SAS concentration (0.15, 0.3 and 0.5 wt%), time (0.5–3 h) and material weight in input (1–10 wt%). High-quality LDPE and aluminium were separated and recovered by using a diluted solution of a surfactant based on lauric acid and triethanolamine (C12-TEA), with performances not achievable with other anionic or cationic surfactants available on the market. The C12-TEA solution was then applied to a large variety of multilayer waste materials composed of polypropylene and aluminium, polyolefins/polyethylene terephthalate/aluminium, giving a material separation dependant on the structure and composition of the material in input. At the end of the process, lauric acid was recovered from the aqueous solution used for washing the separated materials by tuning its water solubility with CO2

Model confidence sets and forecast combination: an application to age-specific mortality

Background: Model averaging combines forecasts obtained from a range of models, and it often produces more accurate forecasts than a forecast from a single model. Objective: The crucial part of forecast accuracy improvement in using the model averaging lies in the determination of optimal weights from a finite sample. If the weights are selected sub-optimally, this can affect the accuracy of the model-averaged forecasts. Instead of choosing the optimal weights, we consider trimming a set of models before equally averaging forecasts from the selected superior models. Motivated by Hansen et al. (2011), we apply and evaluate the model confidence set procedure when combining mortality forecasts. Data & Methods: The proposed model averaging procedure is motivated by Samuels and Sekkel (2017) based on the concept of model confidence sets as proposed by Hansen et al. (2011) that incorporates the statistical significance of the forecasting performance. As the model confidence level increases, the set of superior models generally decreases. The proposed model averaging procedure is demonstrated via national and sub-national Japanese mortality for retirement ages between 60 and 100+. Results: Illustrated by national and sub-national Japanese mortality for ages between 60 and 100+, the proposed model-average procedure gives the smallest interval forecast errors, especially for males. Conclusion: We find that robust out-of-sample point and interval forecasts may be obtained from the trimming method. By robust, we mean robustness against model misspecification

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0\u20135 and 5\u201315 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10\ub0C (mean = 3.0 \ub1 2.1\ub0C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 \ub1 2.3\ub0C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler ( 120.7 \ub1 2.3\ub0C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km <sup>2</sup> resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km <sup>2</sup> pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world\u27s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications