An abstraction and refinement computational approach to safety verification of discrete time nonlinear systems

This paper addresses safety verification of nonlinear systems through invariant set computation. More precisely, our goal is verifying if the state of a given discrete time nonlinear system will keep evolving within a safe region, starting from a given set of initial conditions. To this purpose, we introduce a conformant PieceWise Affine (PWA) abstraction of the nonlinear system, which is instrumental to computing a conservative approximation of its maximal invariant set within the safe region. If the obtained set covers the set of initial conditions, safety is proven. Otherwise, subsequent refinements of the PWA abstraction are performed, either on the whole safe region or on some appropriate subset identified through a guided refinement approach and containing the set of initial conditions. Some numerical examples demonstrate the effectiveness of the approach

The Case of Lionfish (Pterois miles) in the Mediterranean Sea Demonstrates Limitations in EU Legislation to Address Marine Biological Invasions

The European Regulation (EU) 1143/2014 on Invasive Alien Species entered into force in 2015, with the aim to fulfill regional and international biodiversity goals in a concerted manner. To date, the Regulation listed 66 Invasive Alien Species (IAS) that are subject to legal controls. Only one of these is marine. A recent lionfish (Pterois miles) invasion has been closely monitored in the Mediterranean and a detailed risk assessment was made about the profound impacts that this invasive fish is likely to have on the fisheries and biodiversity of the region. In 2016–21, lionfish rapidly became dominant predators along Eastern Mediterranean coasts, yet the process for their inclusion on the EU IAS list has been lengthy and is ongoing. There is an urgent need to learn from this experience. Here, we recommend improvements to the Regulation 1143/2014 and the risk assessment process to protect marine ecosystems and secure the jobs of people that rely on coastal resources.</jats:p

Unpublished Mediterranean and Black Sea records of marine alien, cryptogenic, and neonative species

To enrich spatio-temporal information on the distribution of alien, cryptogenic, and neonative species in the Mediterranean and the Black Sea, a collective effort by 173 marine scientists was made to provide unpublished records and make them open access to the scientific community. Through this effort, we collected and harmonized a dataset of 12,649 records. It includes 247 taxa, of which 217 are Animalia, 25 Plantae and 5 Chromista, from 23 countries surrounding the Mediterranean and the Black Sea. Chordata was the most abundant taxonomic group, followed by Arthropoda, Mollusca, and Annelida. In terms of species records, Siganus luridus, Siganus rivulatus, Saurida lessepsianus, Pterois miles, Upeneus moluccensis, Charybdis (Archias) longicollis, and Caulerpa cylindracea were the most numerous. The temporal distribution of the records ranges from 1973 to 2022, with 44% of the records in 2020–2021. Lethrinus borbonicus is reported for the first time in the Mediterranean Sea, while Pomatoschistus quagga, Caulerpa cylindracea, Grateloupia turuturu, and Misophria pallida are first records for the Black Sea; Kapraunia schneideri is recorded for the second time in the Mediterranean and for the first time in Israel; Prionospio depauperata and Pseudonereis anomala are reported for the first time from the Sea of Marmara. Many first country records are also included, namely: Amathia verticillata (Montenegro), Ampithoe valida (Italy), Antithamnion amphigeneum (Greece), Clavelina oblonga (Tunisia and Slovenia), Dendostrea cf. folium (Syria), Epinephelus fasciatus (Tunisia), Ganonema farinosum (Montenegro), Macrorhynchia philippina (Tunisia), Marenzelleria neglecta (Romania), Paratapes textilis (Tunisia), and Botrylloides diegensis (Tunisia)

Predicting current and future disease outbreaks of Diplodia sapinea shoot blight in Italy: species distribution models as a tool for forest management planning

Species distribution models (SDMs) provide realistic scenarios to explain the influence of bioclimatic variables on plant pathogen distribution. Diplodia sapinea is most harmful to plantations of both exotic and native pine species in Italy, causing economic consequences expecially to edible seed production. In this study, we developed maximum entropy models for D. sapinea in Italy to reach the following goals: (i) to carry out the pathogen’s first geographical distribution analysis in Italy and determine which eco-geographical variables (EGVs) may influence its outbreaks; (ii) to detect the effect of climate change on the potential occurrence of disease outbreaks by 2050 and 2070. We used Maxent ver. 3.4.0 to develop SDMs. We used six global climate models (BCC-CSM1-1, CCSM4, GISS-E2-R, MIROC5, HadGEM2-ES and MPI-ESM-LR) for two representative concentration pathways (4.5 and 8.5) and two time projections (2050 and 2070) to detect future climate projections of D. sapinea. The most important EGVs influencing outbreaks were land cover, altitude, mean temperature of driest and wettest quarter, precipitation of wettest quarter, precipitation seasonality and minimum temperature of coldest month. The distribution of D. sapinea mostly expanded in central and southern Italy and shifted in altitude upwards on average by ca. 93m a.s.l. Moreover the fungus expanded the range where disease outbreaks may be recorded in response to an increase in the mean temperature of wettest and driest quarter by ca. 1.9 °C and 5.8 °C, respectively in all climate change scenarios. Precipitation of wettest quarter did not differ between current and any of future models. Under different climate change scenarios D. sapinea's disease outbreaks will be likely to affect larger areas of pine forests in the country, probably causing heavy effects on the dynamics and evolution of these stands or perhaps constraining their surviva

Modelling risks posed by wind turbines and power lines to soaring birds: the black stork (Ciconia nigra) in Italy as a case study

Recent growth of investments in wind energy and power industries has increased concerns about the associated adverse impacts on wildlife. In particular, flying vertebrates are especially at risk, both directly, through an extra mortality rate due to collision with turbines and electrocution, and indirectly through habitat loss or fragmentation. In this study, we propose a modelling approach that combines species distribution models and data managed in geographic information systems to predict and quantify the effects of wind turbines and power lines on the breeding habitat of a soaring migratory bird, the black stork Ciconia nigra, in Italy. The species is recolonizing the country, where it had been driven to extinction in the Middle Age by human persecution. Today, infrastructures such as those considered in our study might in fact hamper this recolonization. Our results show a high probability of presence of the species in several areas in Italy. The most important variables in influencing habitat suitability for C. nigra are the mean temperature of May followed by the distance from urban areas, inland wetlands and hydrographic network. Exposure to wind turbine collision and electrocution resulted to be potentially high. In particular, in Northern Italy the main potential risk of mortality for C. nigra is posed by power lines, whereas in southern regions the species might be mostly threatened by wind turbines. Our approach makes it possible to detect suitable areas that, although not yet colonized by the species, would imply a high mortality risk should the species colonize them in the future. The tool we provide may therefore prove useful to conservationists and landscape planners in order to mitigate the impact of human infrastructures on this species and encourage a more sustainable planning