Search

Understanding drivers of fish maturity is essential to predict the productivity, stability, and resiliency of exploited populations. Size at maturity for European sardine (Sardina pilchardus) in the Central Mediterranean Sea has never been published within rigorous peer review process. In the past, stock assessment working groups in the Mediterranean requested such information; however, the size at which 50% of the fish population reaches the sexual maturity (L50) often received weak estimates based on a single or few years of observation, which do not necessarily reflect the whole stock. To address this data gap for the Central Mediterranean Sea, the present research estimated size at maturity of European sardine in the Strait of Sicily. In the study period (2009–2017), sampled individuals exhibited significant differences in size range as well as in body condition and reproductive effort. Data also permitted a clear identification of the spawning season, starting in September–October and ending in March–April the following year. Along the analyzed period, the size at first maturity ranged from 108 to 124 mm (total length) for females and from 102 to 122 mm for males. Significant differences were recorded among genders and years. Moreover, a goodness-of-fit measure was proposed to assess the robustness and reliability of L50 estimates, and thus selecting those that minimize the fitting-associated errors. Finally, results suggested that the low proportion of immature individuals in the samples represents the main source of bias in L50 estimation and possible solution was also proposed.

Climate change is causing a structural change in Arctic ecosystems, decreasing the effectiveness that the polar regions have in cooling water masses, with inevitable repercussions on the climate and with an impact on marine biodiversity. The Svalbard islands under study are an area greatly influenced by Atlantic waters. This area is undergoing changes that are modifying the composition and distribution of the species present. The aim of this work is to provide a method for the classification of acoustic patterns acquired in the Kongsfjorden, Svalbard, Arctic Circle using multibeam technology. Therefore the general objective is the implementation of a methodology useful for identifying the acoustically reflective 3D patterns in the water column near the Kronebreen glacier. For each pattern identified, characteristic morphological and energetic quantities were extracted. All the information that describes each of the patterns has been divided into more or less homogeneous groupings by means of a K-means partitioning algorithm. The results obtained from clustering suggest that the most correct interpretation is that which divides the data set into 3 distinct clusters, relating to schools of fish. The presence of 3 different schools of fish does not allow us to state that they are 3 different species. The method developed and implemented in this work is a good method for discriminating the patterns present in the water column, obtained from multibeam data, in restricted contexts similar to those of the study area.

The paper presents sea level and air pressure observations acquired during the 2007 experiment carried out along the southwestern coast of Sicily. The experiment aimed to quantify the atmospheric and oceanic conditions related with the phenomenon of marrobbio, a kind of meteotsunami that is frequently observed in the Strait of Sicily. Sea level data measured at surrounding tide gauges, radio-sounding atmospheric profiles and ERA5 reanalysis data conjoined the analysis. Rapid air pressure and sea level oscillations were measured simultaneously during marrobbio events, while the atmospheric disturbances were estimated to propagate mostly towards east- northeast with a predominant speed of 19–24 m/s. The observed propagation direction and speed were found conducive for generation of long ocean waves through Proudman resonance over a wide outer shelf, although a complex bathymetry in front of affected area may strongly modify the generation. The atmospheric patterns were favourable for wave ducting mechanism during most of the observed marrobbio events. A need for establishing long-term high frequency observations at marrobbio hot spots, as well to apply high-resolution atmospheric and oceanic models for proper quantification of meteotsunamis, is emphasized.

This work presents a computational methodology able to automatically classify the echoes of two krill species recorded in the Ross sea employing scientific echo-sounder at three different frequencies (38, 120 and 200kHz). The goal of classifying the gregarious species represents a time-consuming task and is accomplished by using differences and/or thresholds estimated on the energy features of the insonified targets. Conversely, our methodology takes into account energy, morphological and depth features of echo data, acquired at different frequencies. Internal validation indices of clustering were used to verify the ability of the clustering in recognizing the correct number of species. The proposed approach leads to the characterization of the two krill species (Euphausia superba and Euphausia crystallorophias), providing reliable indications about the species spatial distribution and relative abundance.

The age determination in fast-growing short-living species, such as European anchovy (Engraulis encrasicolus), has been widely recognized as a difficult task and bias introduced by readers leads to bias in reconstructing the population age structure. In this context, it is worth to note that age structure of fish population represents key information in fishery ecology and for stock assessment models. The uncertainty in estimating the age of the European anchovy by otolith reading is linked to the number of false-growth increments (checks) laid down before the annulus formation. While direct validation methods (e.g. mark-recapture, rearing, radiochemical dating) are difficult to implement specially for this short living species, the use of different indirect methods, supported by a coherent statistical approach, represents a robust and easier validation tool. A statistical modeling approach has been here adopted to assess the coherence of two well-known methods, namely Edge Analysis and Marginal Increment Analysis, in order to validate the first annulus formation in European anchovy. Both methodologies in two different yearly cycles converged toward the same result, thus confirming the annulus identification for the first year class. In addition, the completion dates of the checks and the first annulus were computed in order to gain a better insight into otolith growth dynamic. According to the species spawning period, the completion date of the first annulus falls in the summer period, while the first and second checks completion dates were mostly found in summer and winter respectively. General additive models using marginal increments as dependent variable showed a significant effect of the month, highlighting the presence of only one clear minimum in July/August, as well as specific relationships with condition factor and gonadosomatic index. Modeling the otolith edge morphology, the probability to find a hyaline band displayed in both years a similar shape, characterized by a minimum in July/August and higher values between November and January. The obtained results evidenced temporally coherent patterns providing a better insight in the otolith growth dynamic as well as a more robust validation of the first annulus formation in the European anchovy.

Most of the studies carried out in the past on economically important fish species rely on single species approach. Ecosystem dynamics are characterized by complex interaction among species, sharing common habitat needs and thus forming characteristic assemblages. The analysis of spatio-temporal variability of fish community, coupled to the analysis of spatial indices, provides a synthetic view of the fish community status evidencing, if any, the way a community changes. Such considerations drive also to the development of ecosystem-based fishery management paradigm. In the present study changes in pelagic fish community structure in an upwelling ecosystem of the central Mediterranean Sea during the last 10 years was analysed, by focusing the attention on the five most abundant small pelagic species: Engraulis encrasicolus, Sardina pilchardus, Sardinella aurita, Trachurus trachurus and Boops boops. Our results evidenced a quite stable community structure, characterized by spatial occupation strongly driven by ecosystem characteristics and modulated according to specie-specific behaviour. Obtained results lead us to hypothesize that the observed stability of community could be linked to the presence of different environments leading to efficient space partitioning and resources utilization among species.

The study presents the biomass and spatial distribution of Sardinella aurita in the Libyan, Maltese and southern Sicily waters, estimated during four acoustic surveys in summer 2008 and 2010. Strong differences in terms of both spatial distribution and total biomass between years and areas were found, with higher total biomass in 2010 than in 2008 in both southern and northern areas of the central Mediterranean. Habitat suitability and changes in the spatial dynamics of round sardinella among areas and years are then explored in relation to total biomass variation and environmental factors. The area of presence of S. aurita increased in the Maltese and Sicilian waters in 2010 with respect to 2008, while most of the total biomass observed in the two years occupied the same proportion of the continental shelf in Libyan waters. The link between environmental conditions and S. aurita area of presence and aggregation was investigated by means of generalized additive models (GAM). The application of GAM singled out the key role of depth and temperature in driving higher round sardinella aggregations, as they were able to explain in both years about the 48% of total deviance in the case of strictly positive values. Favourable habitat for round sardinella was found in waters shallower than 60 m depths, with a clear peak around 40 m depth. Favourable temperature values were above 22°C for presence/absence case and above 24°C when GAM was applied on strictly positive values. Overall S. aurita biomass and distribution were discussed in the light of the classical models proposed to describe the fish spatial dynamics in relation to an increase in total biomass.

The Common Fisheries Policy of the European Union aims to exploit fish stocks at a level of Maximum Sustainable Yield by 2020 at the latest. At the Mediterranean level, the General Fisheries Commission for the Mediterranean (GFCM) has highlighted the importance of reversing the observed declining trend of fish stocks. In this complex context, it is important to obtain reliable biomass estimates to support scientifically sound advice for sustainable management of marine resources. This paper presents a machine learning methodology for the classification of pelagic species schools from acoustic and environmental data. In particular, the methodology was tuned for the recognition of anchovy, sardine and horse mackerel. These species have a central role in the fishing industry of Mediterranean countries and they are also of considerable importance in the trophic web because they occupy the so-called middle trophic level. The proposed methodology consists of a classifier based on an optimized two layer feed-forward neural network. Morphological, bathymetric, energetic and positional features, extracted from acoustic data, are used as input, together with other environmental data features. The classifier uses an optimal number of neurons in the hidden layer, and a feature selection strategy based on a genetic algorithm. Working on a dataset of 2565 fish schools, the proposed methodology permitted us to identify the these three fish species with an accuracy of around 95%.

The acquisition of oceanographic data for scientific purposes is often quite complex due to the difficulties related to the marine environment. The expensive installation of oceanographic buoys is ...

A 12-year time series (2005–2016) was examined to explore relationships between European anchovy density, growth, reproduction and habitat dynamics in an upwelling system. Specifically, data used for a daily egg production method were combined with oceanographic data, prey availability, as well as acoustic surveys of the anchovy stock in the Strait of Sicily, in the Central Mediterranean Sea. Variables typically used for evaluating habitat dynamics (i.e. water temperature, chlorophyll-a, zooplankton concentration, kinetic energy, mixed layer depth and upwelling index) indicated strong upwelling events during the summer, when anchovy spawns. A linear ‘principal component’ combination of environmental traits, associated with summer upwelling, was identified by step-wise regression as a driver for growth (length at the end of the first year; L1), reproductive investment (gonad-somatic index; GSI), as well as egg production (daily specific fecundity; DSF). These relationships are consistent with direct energy flow from the environment to both somatic growth and reproductive output, indicating an income breeding strategy by anchovy (i.e. surplus energy acquired during the summer breeding season is used directly for reproductive growth). Step-wise regression also identified three additional relationships: (1) a density-dependent mechanism reducing growth (L1) and fecundity (DSF) at higher fish densities; (2) higher fish condition (Kn) positively affecting growth (L1); (3) higher prey availability (mesozooplankton concentration) positively affecting GSI. This time series and approach are promising for exploring the abiotic and biotic mechanisms setting year class strength in advance of recruitment to the fishery.

Fishery production is highly dependent on fish growth and environmental factors; primary production and temperature are the two most important variables affecting almost all biological rates, especially individual growth or population production rate. The growth of European anchovy, Engraulis encrasicolus, was compared between two populations inhabiting different ecosystems: the Tyrrhenian Sea, characterized by riverine inputs and the Strait of Sicily, an oligotrophic area. The effects of habitat conditions on growth was also evaluated using literature data on other of European anchovy populations. Water temperature was confirmed to be a determinant factor for anchovy growth at the species level positively affecting the length at age-1. On the contrary, a negative relationship was found between chlorophyll-a and the length at age-1. These findings suggested that size at age-1 is strongly dependent on habitat conditions. The age structure differed significantly between the two populations, with the Tyrrhenian stock dominated by age-1 fish.

For several years, a group of CNR researchers conducted acoustic surveys in the Sicily Channel to estimate the biomass of small pelagic species, their geographical distribution and their variations over time. The instrument used to carry out these surveys is the scientific echo-sounder, set for different frequencies. The processing of the back scattered signals in the volume of water under investigation determines the abundance of the species. These data are then correlated with the biological data of experimental catches, to attribute the composition of the various fish schools investigated. Of course, the recognition of the fish schools helps to produce very good results, that is very close to the truth about the abundances associated with the various species. In this work, only the acoustic traces of biological monospecific catches, exclusively of two species of pelagic fish. The ecograms where pre-processed using various software tools [1, 2]. For this work, the potential fish schools are detected and isolated using the SHAPES algorithm in Echoview. At the end of the pre-processing phase, the signals are labelled using the two species of pelagic fish: Engraulis encrasicolus and Sardina pilchardus. These labelled signals were used to train a Probabilistic Neural Network (PNN) [3].

A meteorological tsunami, commonly called Meteotsunami, is a tsunami-like wave originated by rapid changes in barometric pressure that involve the displacement of a ody of water. This phenomenon is usually present in the sea cost area of Mazara del Vallo (Sicily, Italy), in particular in the internal part of the seaport canal, sometimes making local population at risk. The Institute for Coastal Marine Environment (IAMC) of the National Research Council in Italy (CNR) have already conducted several studies upon meteotsunami phenomenon. One of the project has regarded the creation of a sensors network composed by micro-barometric sensors, located in 4 different stations close to the seaport of Mazara del Vallo, for the purpose of studying meteotsunami phenomenon. Each station sends all the measurements to a collecting one that elaborates them with the purpose of identifying the direction and speed of pressure fronts. Unfortunately, four stations provide the minimum amount of data necessary to a reliable characterization of pressure fronts so that the failure of only one is a serious issue. Such failures regard blackouts, connection loss, hardware failures or maintenances. In this context we have developed a fault tolerance system that is based on neural networks. A feed forward neural network i is associated with each station i, and is trained to predict its measurements using as inputs the ones of the other three station j with j = i. In the normal condition, the collecting station receives the measurements from each station. In the case of failure of only one station k, the related neural network k can be used to predict the missing measurements. We have conducted preliminary experiments using a two layer feed forward neural network with sigmoid and linear activation functions for the hidden and output layer respectively. In order to simulate failures, we have removed group of data from each station measurements that follow inside a fixed temporal range. The related networks have been used to predict the missing measurements, and the mean square error (MSE) from the real measured value has been computed as performance index. The very low values of obtained MSE lead to the suggestion of a certain effectiveness of the proposed system.

The Strait of Sicily plays a crucial role in determining the water-mass exchanges and related properties between the western and eastern Mediterranean. Hydrographic measurements carried out from 1998 to 2013 allowed the identification of the main water masses present in the Strait of Sicily: a surface layer composed of Atlantic water (AW) flowing eastward, intermediate and deep layers mainly composed of Levantine intermediate water (LIW), and transitional eastern Mediterranean deep water (tEMDW) flowing in the opposite direction. Furthermore, for the first time, the signature of intermittent presence of western intermediate water (WIW) is also highlighted in the northwestern part of the study area (12.235◦ E, 37.705◦ N). The excellent area coverage allowed to highlight the high horizontal and vertical inter-annual variability affecting the study area and also to recognize the permanent character of the main mesoscale phenomena present in the surface water layer. Moreover, strong temperature-salinity correlations in the intermediate layer, for specific time intervals, seem to be linked to the reversal of surface circulation in the central Ionian Sea. The analysis of CTD data in deeper water layer indicates the presence of a large volume of tEMDW in the Strait of Sicily during the summers of 2006 and 2009., peer-reviewed

The pelagic realm of the Central Mediterranean Sea is populated by four main species of fish: sardine, anchovy, horse mackerel and a mix of other pelagic fish species. In this study we employed a multifrequency acoustics approach to detect and classify fish schools of these groups. Monospecific trawl catches were selected from eight acoustic surveys and examined in relation to the coincident acoustic data. The backscattering properties of the three main species were determined using the decibel difference (Sv 120 − Sv 38 ) and the frequency response (NASC 120 /NASC 38 ). The results indicate that schools of these species cannot be distinguished on the basis of energetic properties alone, because they are very similar in physiology and scattering is dominated by the swimbladder, which is similar in shape and size. However, the use of classification models (classification tree, random forest), using energetic features, as well as bathymetric and morphometric parameters, allowed for some discrimination among the groups. According to the classification tree, school depth was found to play an important role in the identification of these fish groups, especially for anchovy and horse mackerel, for which the contribution to the overall performance of the tree was about 20%. The tree models, with only energetic or morphometric parameters, were able to classify sardine schools reasonably well, but not so well for anchovy and horse mackerel. Using a random forest method, which accounted for the variability in the learning sample, an accuracy of 85% in the overall classification rate was reached with a greater power of discrimination for sardine and anchovy schools.

An alternative method to the traditional hydrated oocyte (HO) method has been evaluated for the Sicilian anchovy, Engraulis encrasicolus. The method is based on the processing of ovarian whole mount images and the identification of the spawning batch in oocyte size frequency distributions and shows the advantage that it can be applied to various oocyte stages rather than strictly to the HO stage. Despite the peculiar elliptical shape of anchovy oocytes, this image analysis technique was fully successful since the yolked stage appeared to perform equally to the HO stage for anchovy batch fecundity measurements.

The National Research Council of Italy (CNR) has been undertaking scientific and technological activities aimed at implementing intelligent and automated systems for the collection of data in support of oceanography and fisheries science, as well as providing services for fishing operators. Two independent operational units autonomously developed two original devices, the Fishery Observing System (FOS) and the Information and Communications Technology kit (ICT-kit), recently converging towards a new modular system named the Fishery and Oceanography Observing System (FOOS) that can be adapted to fit the specific research needs of the areas in which it is used. This paper reports the development process and describes the two applications in use in Italy.

Engraulis encrasicolus and Sardina pilchardus stocks are highly variable in terms of recruitment, biomass and spatial distribution. Changes in habitat conditions may influence both the survival of the early life stages and the adult stages. Detailed studies on the spatial distribution and habitat selection of such species have been performed in different areas of the world, highlighting the importance of environmental processes. The present study analyzes the spatial distribution of anchovy and sardine in the Tyrrhenian Sea in relation to environmental heterogeneity. Four acoustic surveys were carried out in this area in the period 2009–2014. Analysis of the environmental dataset permitted identification, in two specific areas, of a pattern of variables driving enrichment processes and impacting on the habitat suitability of the two species. In the northern and central parts of the study area, both anchovy and sardine showed a marked preference for shallower areas characterized by lower salinity. In these areas, PCA results on an environmental dataset highlighted a strong link between primary production, particulate organic carbon, distance from the mouth of the river, salinity and depth. A less clear picture was obtained for the southern part of the Tyrrhenian sea, characterized by a narrow continental shelf, moderately complex coastline morphology and the presence of very small rivers. Most of the anchovy biomass was found to be located in enclosed areas (gulfs) under the influence of relatively small rivers. This finding, taking into account that the surveys were carried out during the anchovy spawning period, highlights for such species a positive effect of the interaction between coastal morphology and riverine input, probably favoring food supply and retention of spawning products.

The physical and chemical processes of the sea greatly affect the reproductive biology of fishes, mainly influencing both the numbers of spawned eggs and the survivorship of early stages up to the recruitment period. In the central Mediterranean, the European anchovy constitutes one of the most important fishery resource. Because of its short living nature and of its recruitment variability, associated to high environmental variability, this small pelagic species undergo high interannual fluctuation in the biomass levels. Despite several efforts were addressed to characterize fishes spawning habitat from the oceanographic point of view, very few studies analyze the air-sea exchanges effects. To characterize the spawning habitat of these resources a specific technique (quotient rule analysis) was applied on air-sea heat fluxes, wind stress, sea surface temperature and turbulence data, collected in three oceanographic surveys during the summer period of 2004, 2005 and 2006. The results showed the existence of preferred values in the examined physical variables, associated to anchovy spawning areas. Namely, for heat fluxes the values were around −40 W/m2, for wind stress 0.04–0.11 N/m2, for SST 23°C, and 300 − 500 m3s−3 for wind mixing. Despite the obtained results are preliminary, this is the first relevant analysis on the air-sea exchanges and their relationship with the fish biology of pelagic species.

In this study, hydroacoustic data collected with a scientific echosounder working at two frequencies (38 and 120 kHz) over the continental shelf off the southern Sicilian coast were used in order to investigate the relationship between fish schools and plankton patches. Specifically, image analysis algorithms were applied to raw echograms in order to detect and characterise pelagic fish schools and plankton aggregations, considered as a proxy of food availability. The relationship was first investigated using estimated total plankton biomass over the whole water column and, second, by dividing the study area into three sub-regions and further distinguishing plankton patches between the surface and the bottom. In the relatively lower plankton abundance areas of Zone 1 (northern sector of the study area), results showed an inverse relationship between the biomass (and density) of fish schools and the biomass of co-occurring plankton patches located close to the bottom. Instead, over the Sicilian-Maltese shelf (Zone 3), characterised by higher plankton abundances, a direct relationship was found when using plankton data from the whole water column. The observed difference between Zones 1 and 3 is probably due to diverse dominant fish species in the two sub-regions.

Hydroacoustic data collected during two echosurveys carried out in the Sicily Channel in 1998 and 2002 were analysed to investigate the distribution and spatial structure of small pelagic fish species in relation to the sedimentological nature of the sea bottom. The study was carried out on two contiguous areas (labelled ZONE 1 and ZONE 2) of the continental shelf off the southern coast of Sicily, characterised by different dominant texture, ‘sand’ for ZONE 1 and ‘clayey-silt’ for ZONE 2. Simultaneous information on small pelagic fish schools and the seabed was obtained using a quantitative echo-sounder (SIMRAD EK500) that measures echoes due to the scattering from both fish schools and the bottom surface. Acoustically determined fish school and seabed data were integrated, respectively, with information on species composition obtained by experimental fishing hauls, and with granulometric information obtained from the analysis of in situ sediment samples. The results indicate a general preference of small pelagic fish schools for seabeds of finer granulometry. First, the occurrence of fish schools was higher over the acoustically classified ‘soft’ seabeds of ZONE 2. Secondly, although ZONE 2 represents 60%) was concentrated over ‘soft’ seabed substrates of ZONE 2. Different species composition and ⁄ or behaviour of fish schools in the two areas investigated were postulated in relation to seabed conditions. Specifically, over the hard and soft bottoms of ZONE 2, fish schools were found at lower depths and at shallower bottom depths compared to ZONE 1. Furthermore, over the softer bottoms of ZONE 2, fish schools exhibiting a more ‘pelagic’ behaviour (i.e. detected at a greater distance from the bottom) showed a preference for softer (and finer) seabed substrate conditions. Conversely, fish schools exhibiting a more ‘demersal’ behaviour (i.e. at a smaller distance from the bottom) were mostly found on relatively harder substrates.

For several years, a group of CNR researchers conducted acoustic surveys in the Sicily Channel to estimate the biomass of small pelagic species, their geographical distribution and their variations over time. The instrument used to carry out these surveys is the scientific echo-sounder, set for different frequencies. The processing of the back scattered signals in the volume of water under investigation determines the abundance of the species. These data are then correlated with the biological data of experimental catches, to attribute the composition of the various fish schools investigated. Of course, the recognition of the fish schools helps to produce very good results, that is very close to the truth about the abundances associated with the various species. In this work, only the acoustic traces of biological monospecific catches, exclusively of two species of pelagic fish. The ecograms where pre-processed using various software tools [1, 2]. For this work, the potential fish schools are detected and isolated using the SHAPES algorithm in Echoview. At the end of the pre-processing phase, the signals are labelled using the two species of pelagic fish: Engraulis encrasicolus and Sardina pilchardus. These labelled signals were used to train a Probabilistic Neural Network (PNN) [3].