The otolith, found in both inner ears of bony fish, has mainly been used to estimate fish age. Another application that has been developing significantly in recent years, however, is the use of otolith shape as a tool for stock identification. Often, studies have directly used the shape asymmetry between the right and left otoliths. We tested the magnitude of directional asymmetry between the sagittal otoliths (left vs. right) of 2991 individuals according to their catch locations, and we selected species to evaluate whether directional asymmetry may itself be a tool to evaluate stock boundaries. Elliptical Fourier descriptors were used to describe the otolith shape. We used a flatfish, the common sole (Solea solea, n = 2431), from the eastern English Channel and the southern North Sea as well as a roundfish, the bogue (Boops boops, n = 560), from the Mediterranean Sea. Both species showed significant levels of directional asymmetry between the testing locations. The bogue otoliths showed significant asymmetry for only 5 out of 11 locations, with substantial separation between two large areas: the Algerian coast and the western part of the Italian coast. The sole otoliths showed significant asymmetry in the shape analysis (3.84–6.57%), suggesting a substantial separation between two large areas: the English and French parts of the English Channel and the southern North Sea. Consequently, directional bilateral asymmetry in otolith shape is a potential new method for stock identification.

Every year, marine scientists around the world read thousands of otolith or scale images to determine the age structure of commercial fish stocks. This knowledge is important for fisheries and conservation management. However, the age-reading procedure is time-consuming and costly to perform due to the specialized expertise and labor needed to identify annual growth zones in otoliths. Effective automated systems are needed to increase throughput and reduce cost. DeepOtolith is an open-source artificial intelligence (AI) platform that addresses this issue by providing a web system with a simple interface that automatically estimates fish age by combining otolith images with convolutional neural networks (CNNs), a class of deep neural networks that has been a dominant method in computer vision tasks. Users can upload otolith image data for selective fish species, and the platform returns age estimates. The estimates of multiple images can be exported to conduct conclusions or further age-related research. DeepOtolith currently contains classifiers/regressors for three fish species; however, more species will be included as related work on ageing will be tested and published soon. Herein, the architecture and functionality of the platform are presented. Current limitations and future directions are also discussed. Overall, DeepOtolith should be considered as the first step towards building a community of marine ecologists, machine learning experts, and stakeholders that will collaborate to support the conservation of fishery resources.

We report new species records and information related to meristic, morphometric, bathymetric and biological characteristics that increase our knowledge of the deep ichthyofauna of the Ionian Sea (E. Mediterranean). The material was collected with long lines from 300 to 800 m deep in the Eastern Ionian Sea in June and October 2010. The fish species Schedophilus ovalis (Cuvier, 1833) (Osteichthyes: Centrolophidae), Sudis hyalina Rafinesque, 1810 (Osteicthyes: Paralepididae), Brama brama (Bonnaterre, 1788) (Osteichthyes: Bramidae) and Trachipterus trachypterus (Gmelin, 1789) (Osteichthyes: Trachipteridae) were recorded for the first time in the Eastern Ionian Sea. The absence of these new or rare species from the ichthyofauna of the study area to date is probably related to the absence of adequate sampling and catching techniques, although environmental factors could also be involved.

The uncertainty in age estimation by otolith reading may be at the root of the large variability in red mullet (Mullus barbatus) growth models in the Mediterranean. In the MEDITS survey, red mullet age data are produced following the same sampling protocol and otolith reading methodology. However, ageing is assigned using different interpretation schemes, including variations in theoretical birthdate and number of false rings considered, in addition to differences in the experience level of readers. The present work analysed the influence of these variations and the geographical location of sampling on red mullet ageing using a multivariate approach (principal component analysis). Reader experience was the most important parameter correlated with the variability. The number of rings considered false showed a significant effect on the variability in the first age groups but had less influence on the older ones. The effect of the theoretical birthdate was low in all age groups. Geographical location had a significant influence, with longitude showing greater effects than latitude. In light of these results, workshops, exchanges and the adoption of a common ageing protocol based on age validation studies are considered fundamental tools for improving precision in red mullet ageing.