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A comprehensive understanding of the concentration of microplastics (MPs) in seawaters is essential to implement monitoring programs and understand the impacts on ecosystems, as required by the European legislation to protect the marine environment. In this context, the purpose of this study is to investigate the composition, quantity, and spatial distribution of microplastics from coastal to offshore areas in three Italian seawaters. In addition, the distribution of microplastics between surface and subsurface water layers was analyzed in order to better understand the dynamics of MPs in the upper layers of the water column. A total number of 6069 MPs (mean total concentration of 0.029 microplastics · m−2) were found to be heterogeneous in type, shape, and color. In general, MPs concentrations decrease with coastal distance, except when environmental forcings are predominant (such as sea currents). Moreover, the amount of surface MPs was almost four times that of subsurface microplastics, which consisted mostly of fibers. In light of these results, it becomes clear how critical it is to plan remediation actions and programs to minimize microplastic accumulations in the sea.

Tobacco smoking is still a widespread habit in pregnant and breastfeeding women. While the role of these risk factors on neonatal outcomes has been deeply studied, their effect on human milk composition is still not completely clear. This study aimed to report the most up to date evidence about the alteration of breast milk composition of smoking breastfeeding mothers compared to non-smoking ones. We performed a systematic review by searching PubMed, Embase, and Cochrane Library databases. Evaluated data were extracted and critically analyzed by two independent authors. PRISMA guidelines were applied, and the risk of bias was assessed (ROBINS), as was the methodological quality of the included studies (GRADE). After applying the inclusion criteria, we included 20 studies assessed as medium or high quality. In all the studies, we analyzed data regarding 1769 mothers (398 smokers and 971 nonsmokers). Smoking was associated with a lower content of lipids, calories, and proteins. Moreover, it was characterized by decreased antioxidant properties and an altered immune status. Smoking during pregnancy and breastfeeding is significantly associated with an alteration of milk metabolic properties. Further studies are needed to investigate how these changes can alter newborns’ development and outcomes and which molecular patterns are involved.

European consumers prefer wild over farmed aquatic food and consider it healthier and tastier. Consumers are increasingly paying attention to sustainability and welfare of farmed fish. Such expecta...

The presence of plastic waste in the marine environment has driven the scientific community to make significant efforts to study and mitigate its possible effects. One of the critical aspects is to determine if and how an increase in ingestion events may occur as a result of the accumulation of plastic waste on the seabed. In this study, G. melastomus is examined for its ability to indirectly provide information on the amount of macroplastics accumulating on the seafloor. Plastic ingestion is explored by describing the feeding habits of the species, which have the potential to provide very useful information regarding biological or ecological issues. The diet of G. melastomus mainly consisted of cephalopods, bathypelagic fishes, and decapod crustaceans, increasing in diversity during growth. The generalist-opportunistic feeding behaviour of this species leads to the incidental ingestion of plastic particles (N = 47, with a mean (± SD) of 1.47 ± 0.28 per specimen) which can be indirectly associated to the presence of macroplastics on the seafloor. Indeed, our results indicate a significant relationship between the amount of macroplastics present on the seabed and the frequency of ingestion of plastic particles by blackmouth catshark. We propose G. melastomus as an excellent candidate for developing a valid monitoring strategy for the presence of plastics on the seabed, as requested by the EU Marine Strategy Framework Directive.

The global need to monitor the status of marine resources is a priority task in marine management, but most ocean surveys still rely on costly and time-consuming capture-based techniques. Here we test a novel, easy-to use device to collect eDNA on board of bottom trawl fishing vessels, during normal fishing operations, quickly and easily: custom-made rolls of gauze tied to a hollow perforated spherical probe (the ‘metaprobe’) that placed inside the fishing net aims to gather traces of genetic material from the surrounding environment. We collected six samples from three central Tyrrhenian sites. Using an established fish-specific metabarcoding marker, we recovered over 70% of the caught species and accurately reconstructed fish assemblages typical of the different bathymetric layers considered. eDNA metabarcoding data also returned a biodiversity ‘bonus’ of mostly mesopelagic species, not catchable by bottom trawls. Further investigation is needed to upscale this promising approach as a powerful tool to monitor catch composition, assess the distribution of stocks, and generally record changes in fish communities across the oceans.

Plastics are one of the most used materials in the world. Their indiscriminate use and inappropriate disposal have led to inevitable impacts, for instance ingestion, on the environment arousing the attention of the global community. In addition, plastic ingestion studies are often written in scientific jargon or hidden behind paywalls, which makes these studies inaccessible. GLOVE is an online and open-access dashboard database available at gloveinitiative.shinyapps.io/Glove/ to support scientists, decision-makers, and society with information collected from plastic ingestion studies. The platform was created in the R environment, with a web interface developed through Shiny. It already comprises 530 studies, including all biological groups, with 245,366 individual records of 1458 species found in marine, freshwater, and terrestrial environments. The main goal of the GLOVE dashboard database is to improve data accessibility by being a scientifically useful grounded tool for designing effective and innovative actions in the current scenario of upcoming global and local agreements and actions on plastic pollution.

Literature often relies on ex post feedbacks from participants to investigate how public participation affects social capital. However, some scholars suggest that the actual achievement of own interests might bias the participants' ex post perception. Therefore, we designed an on‐going evaluative system to monitor the dynamics of trust during public participation, and we tested it in a real case of engagement with local community of stakeholders. The evaluative system could track both processes of creation and destruction of trust over the time, designing complex patterns of evolutions. This study also provided hints for a more effective use of participatory tools. La literatura a menudo se apoya en las retroalimentaciones ex post de los participantes para investigar como afecta la participacion publica al capital social. Sin embargo, algunos investigadores sugieren que el logro real de los propios intereses podria sesgar la percepcion ex post de los participantes. Por lo tanto, se ha disenado un sistema de evaluacion continuo para monitorear la dinamica de la confianza durante la participacion publica, el cual se ha probado en un caso real de involucramiento con la comunidad local de partes interesadas. El sistema de evaluacion podria dar seguimiento tanto a los procesos de creacion como a los de destruccion de la confianza a lo largo del tiempo, mediante el diseno de patrones complejos de evoluciones. Este estudio tambien proporciono pautas para un uso mas eficaz de las herramientas participativas. 研究論文は、市民参加がソーシャル・キャピタルにどのように影響するかを検討するために、参加者からの事後のフィードバックに依存することが多い。しかしながら一部の研究者は、実際に自分の利益を達成することが参加者の事後の認識にバイアスを与える可能性があることを示唆している。そこで、市民参加の際の信頼のダイナミクスを観察する、継続的に評価を行うシステムを作成し、利害関係者の地域コミュニティとの関与における実例においてテストした。この評価システムは、進展の複雑なパターンを描き、信頼の構築と信頼の構築の両方の経過を経時的に追跡することができた。また、本研究から、参加型ツールのより効果的な使用のヒントを得ることができた。

Monitoring marine resource exploitation is a key activity in fisheries science and biodiversity conservation. Since research surveys are time consuming and costly, fishery-dependent data (i.e., derived directly from fishing vessels) are increasingly credited with a key role in expanding the reach of ocean monitoring. Fishing vessels may be seen as widely ranging data-collecting platforms, which could act as a fleet of sentinels for monitoring marine life, in particular exploited stocks. Here, we investigate the possibility of assessing catch composition of single hauls carried out by trawlers by applying DNA metabarcoding to the dense water draining from fishing nets just after the end of hauling operations (hereafter "slush"). We assess the performance of this approach in portraying β-diversity and examining the quantitative relationship between species abundances in the catch and DNA amount in the slush (read counts generated by amplicon sequencing). We demonstrate that the assemblages identified using DNA in the slush satisfactorily mirror those returned by visual inspection of net content (about 71% of species and 86% of families of fish) and detect a strong relationship between read counts and species abundances in the catch. We therefore argue that this approach could be upscaled to serve as a powerful source of information on the structure of demersal assemblages and the impact of fisheries.

Tobacco smoking is still a widespread habit in pregnant and breastfeeding women. While the role of these risk factors on neonatal outcomes has been deeply studied, their effect on human milk composition is still not completely clear. This study aimed to report the most up to date evidence about the alteration of breast milk composition of smoking breastfeeding mothers compared to non-smoking ones. We performed a systematic review by searching PubMed, Embase, and Cochrane Library databases. Evaluated data were extracted and critically analyzed by two independent authors. PRISMA guidelines were applied, and the risk of bias was assessed (ROBINS), as was the methodological quality of the included studies (GRADE). After applying the inclusion criteria, we included 20 studies assessed as medium or high quality. In all the studies, we analyzed data regarding 1769 mothers (398 smokers and 971 nonsmokers). Smoking was associated with a lower content of lipids, calories, and proteins. Moreover, it was characterized by decreased antioxidant properties and an altered immune status. Smoking during pregnancy and breastfeeding is significantly associated with an alteration of milk metabolic properties. Further studies are needed to investigate how these changes can alter newborns' development and outcomes and which molecular patterns are involved.

Marine litter is an ever-increasing problem that demands immediate reduction plans and mitigation actions that should act synergically to efficiently meet ambitious goals. Since the seafloor has been recognized as the major sink for marine debris, the study of litter accumulation dynamics represent a fundamental tool to evaluate possible removal actions. We analysed a 7 years (2013–2019) standardized data series collected along Sardinian fishing grounds through MEDiterranean International Trawl Survey, for which estimates of density and weight of seafloor macro-litter were calculated for over 707 hauls. Results show the absence of any temporal trend in seafloor macro-litter density and weight, but rather indicate a spatial and bathymetric segregation of different litter categories. Our data showed how different sources and physical features of macro-litter items (i.e., plastic and fishing gear, rubber, glass, metals, and cloth) led to spatially segregated accumulation hotspots. We also point out here how the identification of seafloor macro-litter hotspots using aggregated data that include plastic items could obscure the identification of other segregated but yet relevant hotspots of other macro-litter categories accumulated in the marine environment. These hotspots often occurred at shallower depths and closer to coastlines, thus representing potential spots where eventual future litter removal action could be prioritized.

The amount of ingredients of marine origin used in salmonid feed industry is rapidly decreasing and fish meal and fish oil have been largely replaced by vegetable ingredients. New potential protein rich ingredients for aquafeed formulations should therefore be alternative to vegetable ones. The pattern of fillet pigmentation was thus assessed in rainbow trout (Oncorhynchus mykiss) fed for 15 weeks isoproteic (42%) and isolipidic (24%) diets deprived of fish meal where 10% of protein from a blend of vegetable ingredients was replaced by cyanobacteria and microalgae dried biomass (Arthrospira platensis, Tisochrysis lutea and Tetraselmis suecica) or Louisiana red swamp crayfish (Procambarus clarkii) meal. An automatic, repeatable, and objective image analysis tool for the integrated determination and direct visualization of fillet colour was applied to digital images. Colour of fillets was also measured with a chromameter, recording data as L*, a*, b* indexes and used to validate image analysis results. Fillet carotenoid and lipid contents were determined, and their pattern of variation was compared to that obtained by image analysis. Fillet colouring capacity of crayfish meal was also compared to that of commercial synthetic astaxanthin included in rainbow trout feed. To this last aim, test diets were administered for 12 additional weeks. The image analysis and colorimetric data consistently indicated that, even if characterized by a significantly higher carotenoid content respect to fish fed a vegetable diet, fillets of trout fed the cyanobacteria and microalgae including diets displayed an undesirable yellowish colour. P. clarkii meal instead resulted a promising functional ingredient to supplement plant protein-based diets for trout, in view of its lipid composition and astaxanthin content. In fact, despite a relatively low dietary carotenoid level due to low percentage of inclusion, a desirable pink pigmentation was clearly detectable in fillets of trout fed the crayfish meal-including diet, which resulted in colour differences which were less obvious relative to those of fish given the astaxanthin-supplemented feeds at the end of the additional 12 weeks.

17 pages, 10 figures, Current fishing practices often do not allow adequate selection of species or sizes of fish, resulting in unwanted catches, subsequently discarded, with the consequent negative effects on both marine communities and fisheries profitability. The cross-analysis of density patches of potential unwanted catches and distribution of fishing effort can support the identification of spatial-temporal hot-spots in which the fishing pressure should be reduced to limit the amount of discards. The MinouwApp represents a technological and methodological framework to bring different, and structurally complex, sources of georeferenced data together into a simple visual interface aiming to interactively explore temporal ranges and areas of interest. The objective is to improve the understanding of fisheries dynamics, including discards, thus contributing to the implementation of discard management plans in a context of participative, ecosystem-based fisheries management strategies, Open access funding provided by Università degli Studi di Roma Tor Vergata within the CRUI-CARE Agreement. This research has received funding from the European Commission’s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 634495 for the Science, Technology and Society Initiative to Minimize Unwanted Catches in European Fisheries (MINOUW), With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)

In the last decades, the Mediterranean Sea experienced an increasing trend of fish stocks in overfishing status. Therefore, management actions to achieve a more sustainable exploitation of fishery resources are required and compelling. In this study, a spatially explicit multi-species bio-economic modeling approach, namely, SMART, was applied to the case study of central Mediterranean Sea to assess the potential effects of different trawl fisheries management scenarios on the demersal resources. The approach combines multiple modeling components, integrating the best available sets of spatial data about catches and stocks, fishing footprint from vessel monitoring systems (VMS) and economic parameters in order to describe the relationships between fishing effort pattern and impacts on resources and socio-economic consequences. Moreover, SMART takes into account the bi-directional connectivity between spawning and nurseries areas of target species, embedding the outcomes of a larvae transport Lagrangian model and of an empirical model of fish migration. Finally, population dynamics and trophic relationships are considered using a MICE (Models of Intermediate Complexity) approach. SMART simulates the fishing effort reallocation resulting from the introduction of different management scenarios. Specifically, SMART was applied to evaluate the potential benefits of different management approaches of the trawl fisheries targeting demersal stocks (deepwater rose shrimp Parapenaeus longirostris, the giant red shrimp Aristaeomorpha foliacea, the European hake Merluccius merluccius, and the red mullet Mullus barbatus) in the Strait of Sicily. The simulated management scenarios included a reduction of both fishing capacity and effort, two different sets of temporal fishing closures, and two sets of spatial fishing closures, defined involving fishers. Results showed that both temporal and spatial closures are expected to determine a significant improvement in the exploitation pattern for all the species, ultimately leading to the substantial recovery of spawning stock biomass for the stocks. Overall, one of the management scenarios suggested by fishers scored better and confirms the usefulness of participatory approaches, suggesting the need for more public consultation when dealing with resource management at sea.

Technologies within the same industry are expected to follow similar patterns of innovation, and when the dominant patterns change, this is often expected to have disruptive effects on the industry. However, the three most recent lighting technologies (fluorescent, compact fluorescent, and LED) show different patterns of innovative activities despite similarities in the determinants of innovation; and we observed multiple technological regimes within the lighting industry. Furthermore, we observed changes in these innovative patterns without widespread disruptive effects. While FL and LED quickly improved once they were introduced, CFL struggled for decades. We present an historical case study of the emergence and development of the different regimes and we present possible explanations to be found in market structure and selection criteria. The analysis shows the important role for policymakers in stimulating new technologies in industries with undesirable Mark II pattern through the influence of all the dimensions of the technological regimes.

An effective management of trawl fishing should be based on the classification of strategies adopted by fishers in terms of fishing grounds selected and target species. In addition, the dynamics behind strategy selection should be investigated and understood, since they are likely to affect the status of the stocks. This study applies artificial neural networks to identify the main strategies characterizing the fishing activity of Italian trawlers operating in the Central Mediterranean during the period 2009–2016. Moreover, the rationale driving fishers' choice is modelled using General Additive Models (to investigate the role of external factors) and Conditional Logit (to investigate the interaction among fishers). Five strategies were identified together with the potential effects on some key stocks which, in turn, determine the fishers' preference towards alternative strategies. Results suggest that both external factors and interactions are relevant in driving fishers’ behavior, and provide some potentially useful insights for the set-up of management strategies in which the adaptation of fishers to biological and economic factors are explicitly considered.

Sensitivity analysis applied to Artificial Neural Networks (ANNs) as well as to other types of empirical ecological models allows assessing the importance of environmental predictive variables in affecting species distribution or other target variables. However, approaches that only consider values of the environmental variables that are likely to be observed in real-world conditions, given the underlying ecological relationships with other variables, have not yet been proposed. Here, a constrained sensitivity analysis procedure is presented, which evaluates the importance of the environmental variables considering only their plausible changes, thereby exploring only ecological meaningful scenarios. To demonstrate the procedure, we applied it to an ANN model predicting fish species richness, as identifying relationships between environmental variables and fish species occurrence in river ecosystems is a recurring topic in freshwater ecology. Results showed that several environmental variables played a less relevant role in driving the model output when that sensitivity analysis allowed them to vary only within an ecologically meaningful range of values, i.e. avoiding values that the model would never handle in its practical applications. By comparing percent changes in MSE between constrained and unconstrained sensitivity analysis, the relative importance of environmental variables was found to be different, with habitat descriptors and urbanization factors that played a more relevant role according to the constrained procedure. The ecologically constrained procedure can be applied to any sensitivity analysis method for ANNs, but obviously it can also be applied to other types of empirical ecological models.

This paper analyses the distribution patterns of Rome’s spontaneous flora, based on published atlas of species distribution in a grid format. The use of Self-Organizing Map (SOM) makes it possible to recognise and clearly define nine different ecological groups of grid-cells, corresponding to nine different landscape types. The landscape types are characterised by sets of diagnostic species, which are characteristics of the natural environment (soil, climate) and history of urbanisation. This pattern runs counter to the traditional urban-rural gradient, which is the general model of the towns in the Global North; instead it is closer to the still poorly studied towns of the Global South, where urban development is chaotic and unplanned, resulting in a complex urban mosaic of patches with different history and land-use.

Participation is advocated as an essential component of strategies and policies for sustainable urban mobility. This paper refers to the overall literature on participation and provides the design, test and ex-post evaluation of a deliberative-participative procedure (DPP) aimed at selecting a new scheme for the regulation of traffic and parking in the “Murat”, a central area of Bari (Italy). The potential benefits and shortcomings of participation were explicitly considered when designing a DPP which integrates three tools: an opinion poll and two deliberative arenas – the “stakeholder dialogue” and the “citizens’ jury”. The ex-post evaluation of the test confirmed ex-ante design choices. The DPP was effective and learning was generated: the use of understandable techniques for deliberation and assessment helped participants to generate an unambiguous final result which was based on the “hybridisation” of the alternative schemes proposed to the participants at the beginning of the procedure. The “last word” given to the citizens’ jury avoided that the most powerful stakeholders may capture the DPP. Only a “frustration” effect was clearly generated because of the limited involvement of the Municipality of Bari, thus confirming that the involvement of the relevant Authority is an essential requisite for successful participation. We suggest that the generation of new knowledge and learning could be further assured by the participation of citizens and stakeholders to the definition of the alternatives they will assess later.

The discourse of Sustainable Development has reinvigorated the idea that technological innovations are inescapable to sustain economic development and simultaneously achieve environmental sustainability. In this paper, we propose a framework to describe six possible combinations of innovation and demand/consumption levels that constitute in turn six narratives of sustainability. We argue that the present global trend is set out for a dominant narrative, what we call �Green Growth�, which is rooted in the idea that economic growth � and thus technological change � is a prerequisite for environmental sustainability. By way of example, we use the case of the lighting industry to show that this narrative cannot assure an absolute reduction of the present levels of energy consumption. We therefore propose to embrace a different narrative of sustainability that encourages at the same time the development of eco-efficient technologies and the reduction of demand/consumption. This alternative narrative is linked to the development of the concept of �useful light� and to a paradigm change in which the lighting sector is no longer framed around the electric bulb. This transition would require a new class of Lighting Service Companies (LISCO) and of new functional business models based on the sale of �useful light�.

Marine phytoplankton primary production is an extremely important process and its estimates play a major role not only in biological oceanography, but also in a broader context, due to its relationship with oceanic food webs, energy fluxes, carbon cycle and Earth’s climate. The measurement of this process is both expensive and time consuming. Therefore, indirect methods, which can estimate phytoplankton primary production using only remotely sensed predictive information, have many advantages. We describe the development of a depth-resolved model based on an Artificial Neural Network for estimating global phytoplankton primary production. Furthermore, we applied two different approaches, based on input perturbation analysis and on connection weights, to assess the relative importance of the predictive variables. Finally, we compared the results of our depth-resolved model with a previous depth-integrated solution, showing that through the depth-resolution we gained not only useful information on the vertical distribution of the estimated primary production, but also an enhanced accuracy in its depth-integrated estimates.

Species distribution is the result of complex interactions that involve environmental parameters as well as biotic factors. However, methodological approaches that consider the use of biotic variables during the prediction process are still largely lacking. Here, a cascaded Artificial Neural Networks (ANN) approach is proposed in order to increase the accuracy of fish species occurrence estimates and a case study for Leucos aula in NE Italy is presented as a demonstration case. Potentially useful biotic information (i.e. occurrence of other species) was selected by means of tetrachoric correlation analysis and on the basis of the improvements it allowed to obtain relative to models based on environmental variables only. The prediction accuracy of the L. aula model based on environmental variables only was improved by the addition of occurrence data for A. arborella and S. erythrophthalmus. While biotic information was needed to train the ANNs, the final cascaded ANN model was able to predict L. aula better than a conventional ANN using environmental variables only as inputs. Results highlighted that biotic information provided by occurrence estimates for non-target species whose distribution can be more easily and accurately modeled may play a very useful role, providing additional predictive variables to target species distribution models.

Marine litter has significant ecological, social and economic impacts, ultimately raising welfare and conservation concerns. Assessing marine litter hotspots or inferring potential areas of accumulation are challenging topics of marine research. Nevertheless, models able to predict the distribution of marine litter on the seabed are still limited. In this work, a set of Artificial Neural Networks were trained to both model the effect of environmental descriptors on litter distribution and estimate the amount of marine litter in the Central Mediterranean Sea. The first goal involved the use of self-organizing maps in order to highlight the importance of environmental descriptors in affecting marine litter density. The second goal was achieved by developing a multilayer perceptron model, which proved to be an efficient method to estimate the regional quantity of seabed marine litter. Results demonstrated that machine learning could be a suitable approach in the assessment of the marine litter issues.

Toxigenic cyanobacteria are one of the main health risks associated with water resources worldwide, as their toxins can affect humans and fauna exposed via drinking water, aquaculture and recreation. Microscopy monitoring of cyanobacteria in water bodies and massive growth systems is a routine operation for cell abundance and growth estimation. Here we present ACQUA (Automated Cyanobacterial Quantification Algorithm), a new fully automated image analysis method designed for filamentous genera in Bright field microscopy. A pre-processing algorithm has been developed to highlight filaments of interest from background signals due to other phytoplankton and dust. A spline-fitting algorithm has been designed to recombine interrupted and crossing filaments in order to perform accurate morphometric analysis and to extract the surface pattern information of highlighted objects. In addition, 17 specific pattern indicators have been developed and used as input data for a machine-learning algorithm dedicated to the recognition between five widespread toxic or potentially toxic filamentous genera in freshwater: Aphanizomenon, Cylindrospermopsis, Dolichospermum, Limnothrix and Planktothrix. The method was validated using freshwater samples from three Italian volcanic lakes comparing automated vs. manual results. ACQUA proved to be a fast and accurate tool to rapidly assess freshwater quality and to characterize cyanobacterial assemblages in aquatic environments.

The aim of this chapter is to show that the socio-technical map (ST-map) can be useful even to analyze the current and future dynamics of feeding: a societal function that feature complex techno-economic dynamics and contrasting political visions. First of all, the ST systems that are relevant for the today provision of food are considered: the global agribusiness system; the traditional and new local systems; the organic system; the fairtrade system. For each of them a supporting network of innovators is identified; all relevant policies—at the global, national and local scale—are also considered. Then, all food ST systems are positioned into a ST-map based on two dimensions. The first dimension is built on five alternative discourses on sustainable food: ‘Food for all’, ‘Healthy food’, ‘Environment-friendly food’, ‘Food as local culture and local development’, and ‘Food that is produced in a fair way’. The other dimension ranks supply chains from simple to complex: complexity of supply chains depends on both the distance covered and the number of steps. The chapter ends with a future analysis of sustainable food. Starting from ongoing changes and from alternative dynamics of ST-systems and networks of innovators, three scenarios are proposed. The ‘Biotech’ scenario results from a two-fold transition involving the global agribusiness system: suppliers of biotechnological inputs respond to the pressure for sustainable agriculture and food security; large-scale retailers integrate the commercial activity of the organic, fairtrade and local systems. The ‘Elite Versus Mass’ scenario features a new network led by elitist large-scale retailers that clusters the commercial activities of the organic and fair trade systems in order to serve the increasing demand for healthy and environment-friendly food. In the ‘Organic’ scenario a new dominant system integrates all the productive and commercial actors who are interested in converting to organic practices and to organic food products; also some large-scale retailers coming from the global agribusiness system join the organic network. In all scenarios the cumulative process between the empowerment of networks and the emergence of supporting policies is stressed.

In this chapter we analyse the sustainability transition pathway that made Freiburg an ‘Eco-city’ where the modal share of slow mobility is more than 50 % (pedestrians: 24 %; cycling: 28 %), and the car is less relevant (30 %). Through the sequential use of three ST-maps we are able to reconstruct the sustainability transition of Freiburg: from an emerging ‘Auto-city’, where private cars increase of importance (first ST-map: 1969), through a time of coexistence of four different systems (individual car, public transport, individual bicycle, walkability) (second ST-map: 1979), until the polarization in two systems: the individual car and the so-called ‘City of Short Distances’ (third ST-map: 2010). The reproduction of these two systems takes place at different scales: local actors support the ‘City of Short Distances’—which is today dominant in Freiburg—while national and international actors keep supporting the individual car.

In this chapter we show how a socio-technical map (ST-map) can be built in four steps. Graphical examples are taken from the case studies presented in Chaps. 3– 6 of this book. In step 1 the field of analysis is determined: this is usually a whole societal function, such as feeding, housing, mobility. In step 2 the relevant systems and niches and their networks of innovators are identified: the dominant system (if any), other systems, and niches are represented differently into the ST-map. Also local systems and niches—when relevant—can be represented in a specific way. In step 3 the two dimensions of the ST-map are drawned. The first dimension usually represents the relevant political discourses on sustainability, that is, how the current and future sustainability of the analyzed societal function is interpreted by innovators. The second dimension of the ST-map usually represents the techno-economic competences that are leveraged by innovators to promote change. These may refer either to business or productive models, or to technologies. In step 4 all ST systems and niches are positioned into the ST-map. Such a positioning represents to which political discourse and to which techno-economic competence mostly refers the network of innovators of any given system or niche. Also the dominant policy (if any) can be positioned into the ST-map. The resulting ST-map can be used to represent either the current situation of a societal function or its prospective or retrospective dynamics. In the latter case the history of a societal function can be represented through a sequence of ST-maps, each referring to a single moment of relative stability of the societal function. Starting from the current ST-map and from the analysis of the current potential for change also scenarios can be built: these are represented as the result of the ‘demography’ of ST systems and their supportive networks.

In this chapter we show that the socio-technical map (ST-map) can be useful to represent sustainability transitions also when multi-scalar dynamics are at stake. This is the case of urban mobility: it takes place at a local level, but some of its constituents—actors, policies, technologies—are national or global. The analysis starts with the consideration of the ST systems and niches that concur to (and compete for) the provision of urban mobility: the dominant system of the individual car; the subaltern systems of public transport and the bicycle; the emerging carsharing schemes. Also some locally dominant systems of integrated mobility are considered. These systems are then positioned into a ST-map built on two dimensions. The first dimension consider all the relevant political discourses on urban mobility: ‘Mobility as a driver of development’; ‘Mobility as a generator of harmful impacts’; ‘Mobility as a determinant of the quality of urban spaces’; ‘Mobility as a right’. The second dimension lists three alternative business models: ‘sell vehicles’, ‘rent vehicles’, ‘manage transport systems’. Starting from the ST-map of the current situation of urban mobility—and from the consideration of the ongoing changes—three alternative scenarios are proposed. The ‘Auto-city’ scenario emerges from the reconfiguration of the existing ‘individual car’ dominant system and is generated by the absorption of the producers of batteries. In the ‘Eco-city’ scenario a coalition of urban networks supports a new political discourse of urban mobility and foster the creation of new urban systems of integrated mobility. In the ‘Electri-city’ scenario local and national electric operators takes over the individual car system because they are interested in the integration of smart grids and electric vehicles, also in order to increase grid stability and reduce demand-supply unbalances, in particular in the case of renewable sources. Multi-scalar dynamics are at the heart of the proposed scenarios of urban mobility: the ‘Auto-city’ and the ‘Electri-city’ scenarios mostly result from global dynamics, where niches are used for experimentation; the ‘Eco-city’ scenario emerges from a two-dimension diffusion process: horizontally, at the local level, where dominant positions “migrate” from an urban area to another; vertically, from the local to the national level, in order to gain greater political support.

The estimation and quantification of potentially toxic cyanobacteria in lakes and reservoirs are often used as a proxy of risk for water intended for human consumption and recreational activities. Here, we present data sets collected from three volcanic Italian lakes (Albano, Vico, Nemi) that present filamentous cyanobacteria strains at different environments. Presented data sets were used to estimate abundance and morphometric characteristics of potentially toxic cyanobacteria comparing manual Vs. automated estimation performed by ACQUA (“ACQUA: Automated Cyanobacterial Quantification Algorithm for toxic filamentous genera using spline curves, pattern recognition and machine learning” (Gandola et al., 2016) [1]). This strategy was used to assess the algorithm performance and to set up the denoising algorithm. Abundance and total length estimations were used for software development, to this aim we evaluated the efficiency of statistical tools and mathematical algorithms, here described. The image convolution with the Sobel filter has been chosen to denoise input images from background signals, then spline curves and least square method were used to parameterize detected filaments and to recombine crossing and interrupted sections aimed at performing precise abundances estimations and morphometric measurements. Keywords: Comparing data, Filamentous cyanobacteria, Algorithm, Deoising, Natural sample