Age and growth of the bull shark (Carcharhinus leucas) around Reunion Island, South West Indian Ocean.

Sharks exhibit varied demographic strategies depending on both the species and the population location, which make them more or less vulnerable to fishing. Accurate evaluation of local age and growth parameters is therefore fundamental for the sustainable management of their stocks. Although demographic parameters have been assessed for bull shark (Carcharhinus leucas) populations in several locations of the world, this information is missing so far around Reunion Island, in the south-west Indian Ocean. To fill this gap of knowledge, age and growth data were gathered from the vertebrae of 140 individuals of C. leucas (77 females and 63 males, mostly adults) fished around the island between 2012 and 2019. After verification of the annual deposition of growth band pairs on these structures using relative marginal increment analysis on 40 individuals, band pairs were counted along the vertebral centrum for each individual. Thanks to this approach, growth was shown to significantly differ between male and female C. leucas around Reunion Island, with respective von Bertalanffy growth model equations of Lt  =  314 1 - e - 0.0814 t + 5.45 and Lt  = 321.5 1 - e - 0.0999 t + 3.420 . Indeed, the females of the species fished in this area were significantly (P < 0.001) larger than local males, with an estimated difference in size of ~16.1 cm at 20 years old. They also apparently reach older ages, with an estimated maximum age of 33.50 years, against 29.75 years only for the males. The estimated size at birth around the island is larger than elsewhere in the world, varying from 92.30 to 100.00 cm depending on the method used. These results confirm that the population of C. leucas around Reunion Island exhibits a K-selected strategy, which makes it highly vulnerable to fishing pressure.

Otolith chemical fingerprints of skipjack tuna (Katsuwonus pelamis) in the Indian Ocean: First insights into stock structure delineation.

The chemical composition of otoliths (earbones) can provide valuable information about stock structure and connectivity patterns among marine fish. For that, chemical signatures must be sufficiently distinct to allow accurate classification of an unknown fish to their area of origin. Here we have examined the suitability of otolith microchemistry as a tool to better understand the spatial dynamics of skipjack tuna (Katsuwonus pelamis), a highly valuable commercial species for which uncertainties remain regarding its stock structure in the Indian Ocean. For this aim, we have compared the early life otolith chemical composition of young-of-the-year (<6 months) skipjack tuna captured from the three main nursery areas of the equatorial Indian Ocean (West, Central and East). Elemental (Li:Ca, Sr:Ca, Ba:Ca, Mg:Ca and Mn:Ca) and stable isotopic (δ13C, δ18O) signatures were used, from individuals captured in 2018 and 2019. Otolith Sr:Ca, Ba:Ca, Mg:Ca and δ18O significantly differed among fish from different nurseries, but, in general, the chemical signatures of the three nursery areas largely overlapped. Multivariate analyses of otolith chemical signatures revealed low geographic separation among Central and Eastern nurseries, achieving a maximum overall random forest cross validated classification success of 51%. Cohort effect on otolith trace element signatures was also detected, indicating that variations in chemical signatures associated with seasonal changes in oceanographic conditions must be well understood, particularly for species with several reproductive peaks throughout the year. Otolith microchemistry in conjunction with other techniques (e.g., genetics, particle tracking) should be further investigated to resolve skipjack stock structure, which will ultimately contribute to the sustainable management of this stock in the Indian Ocean.

Within-Generation Polygenic Selection Shapes Fitness-Related Traits across Environments in Juvenile Sea Bream.

Understanding the genetic underpinnings of fitness trade-offs across spatially variable environments remains a major challenge in evolutionary biology. In Mediterranean gilthead sea bream, first-year juveniles use various marine and brackish lagoon nursery habitats characterized by a trade-off between food availability and environmental disturbance. Phenotypic differences among juveniles foraging in different habitats rapidly appear after larval settlement, but the relative role of local selection and plasticity in phenotypic variation remains unclear. Here, we combine phenotypic and genetic data to address this question. We first report correlations of opposite signs between growth and condition depending on juvenile habitat type. Then, we use single nucleotide polymorphism (SNP) data obtained by Restriction Associated DNA (RAD) sequencing to search for allele frequency changes caused by a single generation of spatially varying selection between habitats. We found evidence for moderate selection operating at multiple loci showing subtle allele frequency shifts between groups of marine and brackish juveniles. We identified subsets of candidate outlier SNPs that, in interaction with habitat type, additively explain up to 3.8% of the variance in juvenile growth and 8.7% in juvenile condition; these SNPs also explained significant fraction of growth rate in an independent larval sample. Our results indicate that selective mortality across environments during early-life stages involves complex trade-offs between alternative growth strategies.

Molecular approach indicates consumption of jellyfish by commercially important fish species in a coastal Mediterranean lagoon.

Until recently, jellyfish have been ignored as an important source of food, due to their low nutritional value. Here, quantitative PCR was used to detect and quantify the DNA of the jellyfish Aurelia coerulea in the gut contents of commercially important fish species from the Thau Lagoon. Individuals from five fish species were collected during two different periods: the bloom period, when the pelagic stages of A. coerulea are abundant, and the post-bloom period, when only the benthic stage - polyps - is present in the lagoon. The DNA of A. coerulea was detected in the guts of 41.9% of the fish analysed, belonging to four different species. The eel Anguilla anguilla and the seabream Sparus aurata were important jellyfish consumers during the bloom and post-bloom periods, respectively. These results provide new insights on the potential control of jellyfish populations and on jellyfish importance as a food source for exploited fishes.

Modeling larval dispersal for the gilthead seabream in the northwestern Mediterranean Sea.

To investigate dispersal and connectivity between spawning and lagoon nursery habitats of the gilthead seabream, Sparus aurata, in the Gulf of Lions (northwestern Mediterranean Sea), we modeled the potential transport of the species' larvae between its supposed main spawning site in the region (the Planier Island) and two of its main local nursery areas (the coastal lagoons of Thau and Salses-Leucate). Passive larval drift simulations using a dispersal biophysical model showed a large variability in the possible trajectories from spawning to nursery areas and in the predicted ages for larvae arrival on the two nursery sites. The most common ages at arrival obtained in the simulations (20-60 days) are broadly consistent with previous modeling studies but contrast with the actual ages of the S. aurata post-larvae collected in 2016 and 2017 at time of the lagoon entrances (60-90 days, from otolith readings). The period between 25 and 70 days being critical for gilthead seabream larvae to acquire sufficient swimming, osmoregulatory, and olfactory abilities to enter coastal lagoons, we argue that ontogenic development plays a crucial role in the transport and local retention of S. aurata larvae in the studied region, explaining the discrepancy between simulation results and observed data.

Performance of maximum likelihood mixture models to estimate nursery habitat contributions to fish stocks: a case study on sea bream Sparus aurata.

BACKGROUND: Mixture models (MM) can be used to describe mixed stocks considering three sets of parameters: the total number of contributing sources, their chemical baseline signatures and their mixing proportions. When all nursery sources have been previously identified and sampled for juvenile fish to produce baseline nursery-signatures, mixing proportions are the only unknown set of parameters to be estimated from the mixed-stock data. Otherwise, the number of sources, as well as some/all nursery-signatures may need to be also estimated from the mixed-stock data. Our goal was to assess bias and uncertainty in these MM parameters when estimated using unconditional maximum likelihood approaches (ML-MM), under several incomplete sampling and nursery-signature separation scenarios. METHODS: We used a comprehensive dataset containing otolith elemental signatures of 301 juvenile Sparus aurata, sampled in three contrasting years (2008, 2010, 2011), from four distinct nursery habitats. (Mediterranean lagoons) Artificial nursery-source and mixed-stock datasets were produced considering: five different sampling scenarios where 0-4 lagoons were excluded from the nursery-source dataset and six nursery-signature separation scenarios that simulated data separated 0.5, 1.5, 2.5, 3.5, 4.5 and 5.5 standard deviations among nursery-signature centroids. Bias (BI) and uncertainty (SE) were computed to assess reliability for each of the three sets of MM parameters. RESULTS: Both bias and uncertainty in mixing proportion estimates were low (BI ≤ 0.14, SE ≤ 0.06) when all nursery-sources were sampled but exhibited large variability among cohorts and increased with the number of non-sampled sources up to BI = 0.24 and SE = 0.11. Bias and variability in baseline signature estimates also increased with the number of non-sampled sources, but tended to be less biased, and more uncertain than mixing proportion ones, across all sampling scenarios (BI < 0.13, SE < 0.29). Increasing separation among nursery signatures improved reliability of mixing proportion estimates, but lead to non-linear responses in baseline signature parameters. Low uncertainty, but a consistent underestimation bias affected the estimated number of nursery sources, across all incomplete sampling scenarios. DISCUSSION: ML-MM produced reliable estimates of mixing proportions and nursery-signatures under an important range of incomplete sampling and nursery-signature separation scenarios. This method failed, however, in estimating the true number of nursery sources, reflecting a pervasive issue affecting mixture models, within and beyond the ML framework. Large differences in bias and uncertainty found among cohorts were linked to differences in separation of chemical signatures among nursery habitats. Simulation approaches, such as those presented here, could be useful to evaluate sensitivity of MM results to separation and variability in nursery-signatures for other species, habitats or cohorts.

Listening in on the past: what can otolith δ18O values really tell us about the environmental history of fishes?

Oxygen isotope ratios from fish otoliths are used to discriminate marine stocks and reconstruct past climate, assuming that variations in otolith δ18O values closely reflect differences in temperature history of fish when accounting for salinity induced variability in water δ18O. To investigate this, we exploited the environmental and migratory data gathered from a decade using archival tags to study the behaviour of adult plaice (Pleuronectes platessa L.) in the North Sea. Based on the tag-derived monthly distributions of the fish and corresponding temperature and salinity estimates modelled across three consecutive years, we first predicted annual otolith δ18O values for three geographically discrete offshore sub-stocks, using three alternative plausible scenarios for otolith growth. Comparison of predicted vs. measured annual δ18O values demonstrated >96% correct prediction of sub-stock membership, irrespective of the otolith growth scenario. Pronounced inter-stock differences in δ18O values, notably in summer, provide a robust marker for reconstructing broad-scale plaice distribution in the North Sea. However, although largely congruent, measured and predicted annual δ18O values did not fully match [ corrected]. Small, but consistent, offsets were also observed between individual high-resolution otolith δ18O values measured during tag recording time and corresponding δ18O predictions using concomitant tag-recorded temperatures and location-specific salinity estimates. The nature of the shifts differed among sub-stocks, suggesting specific vital effects linked to variation in physiological response to temperature. Therefore, although otolith δ18O in free-ranging fish largely reflects environmental temperature and salinity, we counsel prudence when interpreting otolith δ18O data for stock discrimination or temperature reconstruction until the mechanisms underpinning otolith δ18O signature acquisition, and associated variation, are clarified.

Selecting statistical models and variable combinations for optimal classification using otolith microchemistry.

Reliable assessment of fish origin is of critical importance for exploited species, since nursery areas must be identified and protected to maintain recruitment to the adult stock. During the last two decades, otolith chemical signatures (or "fingerprints") have been increasingly used as tools to discriminate between coastal habitats. However, correct assessment of fish origin from otolith fingerprints depends on various environmental and methodological parameters, including the choice of the statistical method used to assign fish to unknown origin. Among the available methods of classification, Linear Discriminant Analysis (LDA) is the most frequently used, although it assumes data are multivariate normal with homogeneous within-group dispersions, conditions that are not always met by otolith chemical data, even after transformation. Other less constrained classification methods are available, but there is a current lack of comparative analysis in applications to otolith microchemistry. Here, we assessed stock identification accuracy for four classification methods (LDA, Quadratic Discriminant Analysis [QDA], Random Forests [RF], and Artificial Neural Networks [ANN]), through the use of three distinct data sets. In each case, all possible combinations of chemical elements were examined to identify the elements to be used for optimal accuracy in fish assignment to their actual origin. Our study shows that accuracy differs according to the model and the number of elements considered. Best combinations did not include all the elements measured, and it was not possible to define an ad hoc multielement combination for accurate site discrimination. Among all the models tested, RF and ANN performed best, especially for complex data sets (e.g., with numerous fish species and/or chemical elements involved). However, for these data, RF was less time-consuming and more interpretable than ANN, and far more efficient and less demanding in terms of assumptions than LDA or QDA. Therefore, when LDA and QDA assumptions cannot be reached, the use of machine learning methods, such as RF, should be preferred for stock assessment and nursery identification based on otolith microchemistry, especially when data set include multispecific otolith signatures and/or many chemical elements.

Trophodynamic linkage between river runoff and coastal fishery yield elucidated by stable isotope data in the Gulf of Lions (NW Mediterranean).

The link between climate-driven river runoff and sole fishery yields observed in the Gulf of Lions (NW Mediterranean) was analysed using carbon- and nitrogen stable isotopes along the flatfish food webs. Off the Rhone River, the main terrestrial (river POM) and marine (seawater POM) sources of carbon differed in delta(13)C (-26.11 per thousand and -22.36 per thousand, respectively). Surface sediment and suspended POM in plume water exhibited low delta(13)C (-24.38 per thousand and -24.70 per thousand, respectively) that differed more from the seawater POM than from river POM, demonstrating the dominance of terrestrial material in those carbon pools. Benthic invertebrates showed a wide range in delta(15)N (mean 4.30 per thousand to 9.77 per thousand ) and delta(13)C (mean -23.81 per thousand to -18.47 per thousand ), suggesting different trophic levels, diets and organic sources. Among the macroinvertebrates, the surface (mean delta(13)C -23.71 per thousand ) and subsurface (mean delta(13)C -23.81 per thousand ) deposit-feeding polychaetes were particularly (13)C depleted, indicating that their carbon was mainly derived from terrestrial material. In flatfish, delta(15)N (mean 9.42 to 10.93 per thousand ) and delta(13)C (mean -19.95 per thousand to -17.69 per thousand ) varied among species, indicating differences in food source and terrestrial POM use. A significant negative correlation was observed between the percentage by weight of polychaetes in the diet and the delta(13)C of flatfish white muscle. Solea solea (the main polychaete feeder) had the lowest mean delta(13)C, Arnoglossus laterna and Buglossidium luteum (crustacean, mollusc and polychaete feeders) had intermediate values, and Solea impar (mollusc feeder) and Citharus linguatula (crustacean and fish feeder) exhibited the highest delta(13)C. Two different benthic food webs were thus identified off the Rhone River, one based on marine planktonic carbon and the other on the terrestrial POM carried by the river. Deposit-feeding polychaetes were responsible for the main transfer of terrestrial POM to upper trophic levels, linking sole population dynamics to river runoff fluctuations.

Fluctuations of macrobenthic populations: a link between climate-driven river run-off and sole fishery yields in the Gulf of Lions.

The Rhone river is the most important input to the Mediterranean Sea, responsible for 50% of the primary productivity of the Gulf of Lions. A highly variable amount of 1-23×106 t year-1 of terrestrial material is exported to the sea by the Rhone and stocked on the continental shelf for the most part. Soft-bottom communities off the Rhone delta were dominated by polychaetes both in species richness and abundance, and exhibited strong temporal fluctuations mainly related to flooding events. Floods caused pulses of organic matter followed, with different time lags, by peaks of polychaetes. Opportunistic, short-lived species, such as Mediomastus sp. and Aricidea claudiae, exhibited high short-term peaks in density and biomass a few months after flooding events. Conversely, long-lived species, such as Laonice cirrata and Sternaspis scutata, peaked in density and biomass with a time lag of 1-3 years, and their population increase lasted for a few years. The common sole, Solea solea, is a voracious predator of polychaetes which represent >80% of its prey. A positive correlation was found between the mean annual discharge of the Rhone river and the annual commercial landings of S. solea with a time lag of 5 years in the two fishing harbours (Sete and Martigues) located close to the Rhone delta. The long-term increase in food (i.e. polychaete density and biomass) after flooding events might favour the different stages of the sole life cycle, enhancing its population size for several years. Fluctuations of sole fishery yields in the Gulf of Lions could be influenced by climate, as the Rhone river flow is related to the North Atlantic Oscillation that drives precipitation over Western Europe.