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Fishery Observing System (FOS) was developed as a first and basic step towards fish stock abundance nowcasting/forecasting within the framework of the EU research program Mediterranean Forecasting System: Toward an Environmental Prediction (MFSTEP). The study of the relationship between abundance and environmental parameters also represents a crucial point towards forecasting. Eight fishing vessels were progressively equipped with FOS instrumentation to collect fishery and oceanographic data. The vessels belonged to different harbours of the Central and Northern Adriatic Sea. For this pilot application, anchovy (Engraulis encrasicolus, L.) was chosen as the target species. Geo-referenced catch data, associated with in-situ temperature and depth, were the FOS products but other parameters were associated with catch data as well. MFSTEP numerical circulation models provide many of these data. In particular, salinity was extracted from re-analysis data of numerical circulation models. Satellite-derived sea surface temperature (SST) and chlorophyll were also used as independent variables. Catch and effort data were used to estimate an abundance index (CPUE – Catch per Unit of Effort). Considering that catch records were gathered by different fishing vessels with different technical characteristics and operating on different fish densities, a standardized value of CPUE was calculated. A spatial and temporal average CPUE map was obtained together with a monthly mean time series in order to characterise the variability of anchovy abundance during the period of observation (October 2003–August 2005). In order to study the relationship between abundance and oceanographic parameters, Generalized Additive Models (GAM) were used. Preliminary results revealed a complex scenario: the southern sector of the domain is characterised by a stronger relationship than the central and northern sector where the interactions between the environment and the anchovy distribution are hidden by a higher percentage of variability within the system which is still unexplained. GAM analysis showed that increasing the number of explanatory variables also increased the portion of variance explained by the model. Data exchange and interdisciplinary efforts will therefore be crucial for the success of this research activity.

The paper presents information on the burrows of a number of species that occur on Squilla grounds in the coastal Adriatic off Ancona, Italy. The burrows and burrowing behaviour of Brachynotus gemmellari are described for the first time. For Upogebia tipica, Solecurtus strigilatus and Gobius niger, the observations add to sparse burrow information in the literature. Little is known of the burrows of Echiura in the Mediterranean: those of two species are briefly described from surface features.

Abundance and distribution of commercial marine resources are influenced by environmental variables, which together with fishery patterns may also influence their catchability. However, Catch Per Unit Effort (CPUE) can be standardized in order to remove most of the variability not directly attributable to fish abundance. In the present study, Generalized Additive Models (GAMs) were used to investigate the effect of some environmental and fishery covariates on the spatial distribution and abundance of the Norway lobster Nephrops norvegicus within the Pomo/Jabuka Pits (Central Adriatic Sea) and to include those that resulted significant in a standardization process. N. norvegicus is a commercially important demersal crustacean, altering its catchability over the 24-h cycle and seasons according to its burrowing behavior. A historically exploited fishing ground for this species, since 2015 subject to specific fisheries management measures, is represented by the meso-Adriatic depressions, which are also characterized by particular oceanographic conditions. Both the species behaviour and the features of this study area influence the dynamics of the population offering a challenging case study for a standardization modelling approach. Environmental and catch data were obtained during scientific trawl surveys properly designed to catch N. norvegicus, thus improving the quality of the model input data. Standardization of CPUE from 2 surveys from 2012 to 2019 was conducted building two GAMs for both biomass and density indices. Bathymetry, fishing pressure, dissolved oxygen and salinity proved to be significant drivers influencing catch distribution. After cross validations, the tuned models were then used to predict new indices for the study area and the two survey series by means of informed spatial grids, composed by constant surface cells, to each of which are associated average values of environmental parameters and specific levels of fishing pressure, depending on the management measures in place. The predictions can be used to better describe the structure and the spatio-temporal distribution of the population providing valuable information to evaluate the status of such an important marine resource., Competing Interests: The authors have declared that no competing interests exist.

This corrects the article DOI: 10.1038/sdata.2017.104.

Using thirteen microsatellite loci for Mullus barbatus and Mullus surmuletus collected in the Mediterranean Sea, the biogeographic boundaries, genetic distribution among and within basins and the impact of prolonged exploitation in both species were investigated as a basis for understanding their population dynamics and for improving Mullus spp. stock management. Different level of diversity indices among these co-occurring species were obtained, with M. barbatus showing higher allele richness and higher mean observed and expected heterozygosity than M. surmuletus. Reduced contemporary effective population size (Ne) and M-ratio values found in both species likely reflects recent demographic changes, due to a combination of high fishing pressures, habitat fragmentation and naturally occurring fluctuations in population size. Different patterns of genetic connectivity among populations sampled within the Mediterranean were observed for both species. Higher genetic structure was found for M. barbatus as opposed to a more homogenous pattern observed in M. surmuletus samples. Adriatic populations, previously considered panmictic and isolated from other Mediterranean regions, showed geographical partitioning within the basin but also population connectivity with the northern Ionian and Tyrrhenian Seas. Our results highlight the need for temporal sampling in understanding the complex pattern of population connectivity in the Mediterranean, particularly for management purposes.

Historic data on biodiversity provide the context for present observations and allow studying long-term changes in marine populations. Here we present multiple datasets on fish and fisheries of the Adriatic Sea covering the last two centuries encompassing from qualitative observations to standardised scientific monitoring. The datasets consist of three groups: (1) early naturalists' descriptions of fish fauna, including information (e.g., presence, perceived abundance, size) on 255 fish species for the period 1818-1936; (2) historical landings from major Northern Adriatic fish markets (Venice, Trieste, Rijeka) for the period 1902-1968, Italian official landings for the Northern and Central Adriatic (1953-2012) and landings from the Lagoon of Venice (1945-2001); (3) trawl-survey data from seven surveys spanning the period 1948-1991 and including Catch per Unit of Effort data (kgh -1 and/or nh -1 ) for 956 hauls performed at 301 stations. The integration of these datasets has already demonstrated to be useful to analyse historical marine community changes over time, and its availability through open-source data portal will facilitate analyses in the framework of marine historical ecology.

The sustained exploitation of marine populations requires an understanding of a species' adaptive seascape so that populations can track environmental changes from short- and long-term climate cycles and from human development. The analysis of the distributions of genetic markers among populations, together with correlates of life-history and environmental variability, can provide insights into the extent of adaptive variation. Here, we examined genetic variability among populations of mature European anchovies (n = 531) in the Adriatic (13 samples) and Tyrrhenian seas (2 samples) with neutral and putative non-neutral microsatellite loci. These genetic markers failed to confirm the occurrence of two anchovy species in the Adriatic Sea, as previously postulated. However, we found fine-scale population structure in the Adriatic, especially in northern areas, that was associated with four of the 13 environmental variables tested. Geographic gradients in sea temperature, salinity and dissolved oxygen appear to drive adaptive differences in spawning time and early larval development among populations. Resolving adaptive seascapes in Adriatic anchovies provides a means to understand mechanisms underpinning local adaptation and a basis for optimizing exploitation strategies for sustainable harvests.

It is well known that temporal fluctuations in small populations deeply influence evolutionary potential. Less well known is whether fluctuations can influence the evolutionary potentials of species with large census sizes. Here, we estimated genetic population parameters from as survey of polymorphic microsatellite DNA loci in archived otoliths from Adriatic European anchovy (Engraulis encrasicolus), a fish with large census sizes that supports numerous local fisheries. Stocks have fluctuated greatly over the past few decades, and the Adriatic fishery collapsed in 1987. Our results show a significant reduction of mean genetic parameters as a consequence of the population collapse. In addition, estimates of effective population size (Ne) are much smaller than those expected in a fishes with large population census sizes (Nc). Estimates of Ne indicate low effective population sizes, even before the population collapse. The ratio Ne/Ne ranged between 10-6 and 10-8, indicating a large discrepancy between the anchovy gene pool and population census size. Therefore, anchovy populations may be more vulnerable to fishery effort and environmental change than previously thought.