Estimating preferences for controlling beach erosion in Sicily

This study applied discrete-choice experiments to estimate preferences for a program aimed at reducing the retreatment of the sandy beach at "Lido di Noto", a renowned Sicilian bathing resort close to Noto (Italy). Econometric analysis of data was based on Multinomial Logit (MNL), Latent Class (LC) and Mixed Logit (MXL) models. Findings shown that users appreciated the advancement of the current coastline through nourishment, and negatively perceived the construction of emerged sea barriers. MXL and LC models revealed that preferences were heterogeneous

Assessing the hidden impacts of hypothetical eruption events at Mount Etna

Abstract We estimate how the value and the spatial distribution of carbon storage, water yield and wild pollination services are expected to change with potential expansion of lava flow inundation at Mount Etna volcano (Sicily, Italy). We rely on a hazard map lava by flow inundation to simulate a set of three future land use/land cover (LU/LC) scenarios related to different hazard levels with a specific probability of occurrence. Our assessment used the Integrated Valuation of Environmental Services and Tradeoffs (InVEST) tool and GIS spatial analysis and indicates that changes in the delivery of all three ecosystem services are biophysically and economically sizeable. The variation between scenarios demonstrates that the carbon storage and wild pollination services will decrease because of the loss of woods and natural habitats. In contrast, the water yield capacity will increase for the creation of new naked land surfaces characterised by high permeability values. In the worst-case scenario, we estimate a loss of 17% and 10% for carbon storage and wild pollination services respectively, and an increase of approximately 10% for water yield

Distribution and natural history of Plutonium zwierleini (Chilopoda: Scolopendromorpha) in Sicily (Italy)

Plutonium zwierleini is a large plutoniumid centipede of great evolutionary interest, occurring with isolated populations along the western Mediterranean area, from Spain to Italy. Due to its rarity and the extreme paucity of available records, P. zwierleini is among the least known Mediterranean chilopods, and scarce information is currently available on its ecology and natural history. Based on an extensive sampling effort carried out in Sicily between 2022 and 2023, we here provide additional occurrence localities for the species across Sicily, and new insights into its ecology. Overall, 29 novel Sicilian records of P. zwierleini, scattered across 21 localities, were collected thus increasing its known Sicilian distribution area by 117%, and the number of localities by 110%. The species was found in a wide range of habitats such as open areas, woods, buildings, and caves, characterizing Plutonium zwierleini as a habitat generalist, whose fine ecological preferenda need to be further explored. Moreover, to explore the diet and behaviour of the species, some specimens were kept in captivity. The captive individuals fed mostly on dead or poorly mobile soft-bodied prey and inert food, without ever displaying predatory behaviour; this suggests that, contrarily to what is currently assumed, P. zwierleini might be a scavenger rather than a predator. The potential distribution of Plutonium zwierleini in Sicily was inferred based on georeferenced occurrence records and climatic variables. The implemented MaxEnt model forecasts the possible occurrence of P. zwierleini on the whole island, with the single exception of its south-easternmost part, possibly due to the local pattern of precipitation seasonality. We hope that the present work might pave the way for further surveys aimed at a better understanding of the ecology of Plutonium zwierleini and the collection of new data in the other regions inhabited by this secretive species

Fire risk modeling: an integrated and data-driven approach applied to Sicily

Wildfires are key not only to landscape transformation and vegetation succession, but also to socio-ecological values loss. Fire risk mapping can help to manage the most vulnerable and relevant ecosystems impacted by wildfires. However, few studies provide accessible daily dynamic results at different spatio-temporal scales. We develop a fire risk model for Sicily (Italy), an iconic case of the Mediterranean Basin, integrating a fire hazard model with an exposure and vulnerability analysis under present and future conditions. The integrated model is data-driven but can run dynamically at a daily time step, providing spatially and temporally explicit results through the k.LAB (Knowledge Laboratory) software. This software provides an environment for input data integration, combining methods and data such as geographic information systems, remote sensing and Bayesian network algorithms. All data and models are semantically annotated, open and downloadable in agreement with the FAIR principles (findable, accessible, interoperable and reusable). The fire risk analysis reveals that 45 % of vulnerable areas of Sicily have a high probability of fire occurrence in 2050. The risk model outputs also include qualitative risk indexes, which can make the results more understandable for non-technical stakeholders. We argue that this approach is well suited to aiding in landscape and fire risk management, under both current and climate change conditions.</p

Are protected areas covering important biodiversity sites? An assessment of the nature protection network in Sicily (Italy)

GIS spatial analysis of three indicators (vegetation value, faunal richness and landscape heterogeneity) was used to detect and map High-Value Biodiversity Areas (HVBAs), estimate the coverage of biodiversity in the Sicilian protected areas network, and identify new priority areas that could improve long-term biodiversity conservation outcomes. Findings indicated that only 32% of HVBAs are currently covered by the protected areas network. Hotspot analysis revealed that a modest expansion (less than 1%) in the current extent of protected areas would include a disproportionate amount (56%) of biodiversity hotspots, and identified prioritized candidates HVBAs for designation of new protected areas. © 2018 Elsevier Lt