French Research Institute for Exploitation of the Sea
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Seasonality and interannual stability in the population genetic structure of Batrachospermum gelatinosum (Rhodophyta)
No full textTemporal population genetic studies have investigated evolutionary processes, but few have characterized reproductive system variation. Yet, temporal sampling may improve our understanding of reproductive system evolution through the assessment of the relative rates of selfing, outcrossing, and clonality. In this study, we focused on the monoicous, haploid‐diploid freshwater red alga Batrachospermum gelatinosum. This species has a perennial, microscopic diploid phase (chantransia) that produces an ephemeral, macroscopic haploid phase (gametophyte). Recent work focusing on single‐time point genotyping suggested high rates of intragametophytic selfing, although there was variation among sites. We expand on this work by genotyping 191 gametophytes sampled from four sites that had reproductive system variation based on single‐snapshot genotyping. For this study, we sampled at multiple time points within and among years. Results from intra‐annual data suggested shifts in gametophytic genotypes throughout the season. We hypothesize that this pattern is likely due to the seasonality of the life cycle and the timing of meiosis among the chantransia. Interannual patterns were characterized by consistent genotypic and genetic composition, indicating stability in the prevailing reproductive system through time. Yet, our study identified limits by which available theoretical predictions and analytical tools can resolve reproductive system variation using haploid data. There is a need to develop new analytical tools to understand the evolution of sex by expanding our ability to characterize the spatiotemporal variation in reproductive systems across diverse life cycles
Neural Synthetic Profiles from Remote Sensing and Observations (NeSPReSO) -Reconstructing temperature and salinity fields in the Gulf of Mexico
No full textAccurate circulation modeling in the Gulf of Mexico (GoM) is hampered by the limited availability of in-situ subsurface data, leading to inaccuracies in subsurface representations. These inaccuracies diminish the reliability of ocean models and constrain the duration of dependable forecasts. This study introduces NeSPReSO (Neural Synthetic Profiles from Remote Sensing and Observations), a data-driven method to efficiently and accurately estimate subsurface temperature and salinity profiles using satellite-derived surface data. This provides an alternative to conventional synthetic data generation techniques.
Principal Component Analysis (PCA) is applied to extract the main features of temperature and salinity profiles of an Argo dataset. Then, a neural network is trained to predict these principal features using inputs such as time, location, and satellite-derived absolute dynamic topography alongside sea surface temperature and salinity. The model, evaluated using additional Argo profiles and glider data collected in the Gulf of Mexico, over-performs other traditional synthetic data generation methods, such as the Gravest Empirical Modes (GEM), Multiple Linear Regression (MLR) and Improved Synthetic Ocean Profile (ISOP), in terms of root mean square error and bias. Our findings indicate that our method effectively captures the main variations of subsurface fields, and that synthetic profiles generated by the model align well with actual observations, accurately capturing key features such as thermoclines, haloclines, and temperature-salinity structure of the region. This new method will be implemented in GoM data assimilative models and is expected to improve the accuracy of modeled subsurface currents
Deep-learning-based detection of underwater fluids in multiple multibeam echosounder data
No full textetecting and locating emitted fluids in the water column is necessary for studying margins, identifying natural resources, and preventing geohazards. Fluids can be detected in the water column using multibeam echosounder data. However, manually analyzing the huge volume of this data for geoscientists is a very time-consuming task. Our study investigated the use of a YOLO-based deep learning supervised approach to automate the detection of fluids emitted from cold seeps (gaseous methane) and volcanic sites (liquid carbon dioxide). Several thousand annotated echograms collected from three different seas and oceans during distinct surveys were used to train and test the deep learning model. The results demonstrate first that this method surpasses current machine learning techniques, such as Haar-Local Binary Pattern Cascade. Additionally, we thoroughly analyzed the composition of the training dataset and evaluated the detection performance based on various training configurations. The tests were conducted on a dataset comprising hundreds of thousands of echograms i) acquired with three different multibeam echosounders (Kongsberg EM302 and EM122 and Reson Seabat 7150) and ii) characterized by variable water column noise conditions related to sounder artefacts and the presence of biomass (fishes, dolphins). Incorporating untargeted echoes (acoustic artefacts) in the training set (through hard negative mining) along with adding images without fluid-related echoes are the most efficient way to improve the performance of the model and reduce the false positives. Our fluid detector opens the door for near-real time acquisition and post-acquisition detection with efficiency, reliability and rapidity
Not just mutations: Inbreeding depression persists without genetic variation
No full textInbreeding depression (ID), the decline in fitness upon inbreeding, is thought to result from a decrease in genetic heterozygosity enhancing phenotypic effects of recessive deleterious mutations. However, emerging evidence suggests that mutations may not explain ID completely. In this study, we test whether ID can emerge even in contexts where genetic heterozygosity does not vary. To that end, highly inbred lines (F=0.99999997) of the freshwater snail Physa acuta were used to produce individuals with varying levels of parental relatedness (self-fertilization, sibling crosses, and cousin crosses), though with identical genomic heterozygosity. Several fitness traits declined significantly with increasing parental relatedness, a pattern characteristic of ID, and quantitatively representing a non-negligible fraction of the ID usually observed in natural, genetically diverse populations of Physa acuta. Individual-based simulations showed that mutation rates compatible with values of ID found in natural populations are way too low to generate as much ID as observed in our experiment. These findings are consistent with the hypothesis that epigenetic changes, in addition to mutations, could contribute to a rapid regeneration of ID and explain the persistence of detectable ID in sets of genetically identical individuals
Asymmetrical Ocean Carbon Responses in the Tropical Pacific Ocean to La Niña and El Niño
No full textAsymmetrical ocean carbon responses to La Ni & ntilde;a and El Ni & ntilde;o complicate global carbon budget estimation. Using multiple ocean CO2 data products and an advanced ocean biogeochemical model, we identified significant asymmetries in ocean carbon magnitude, spatial distribution, and duration in the tropical Pacific Ocean. La Ni & ntilde;a enhances ocean CO2 outgassing (0.1-0.2 PgC/yr) with a broader poleward extension (15 degrees S-15 degrees N) for up to 3 years, while El Ni & ntilde;o reduces outgassing (0.2-0.4 PgC/yr) with a narrower poleward extension (10 degrees S-10 degrees N) for up to 1 year. The air-sea carbon flux anomaly shifts westward during La Ni & ntilde;a and eastward during El Ni & ntilde;o. These asymmetries are attributed to differing wind, precipitation, and ocean circulation anomalies between La Ni & ntilde;a and El Ni & ntilde;o. Additionally, the cumulative carbon flux remains slightly imbalanced, impacting the global ocean carbon sink balance. This study provides deeper insights into ocean carbon sink variability and highlights the need for enhanced monitoring of asymmetrical ocean carbon dynamics. Plain Language Summary The El Ni & ntilde;o-Southern Oscillation (ENSO) is a dominant factor in the interannual variation of global air-sea CO2 flux. In the ocean, ENSO manifests itself as a transition between El Ni & ntilde;o and La Ni & ntilde;a. Because of the asymmetry between the two, it may exert a non-zero forcing, inducing imbalanced carbon responses to ENSO. In this study, we have studied the asymmetry of air-sea CO2 flux caused by La Ni & ntilde;a and El Ni & ntilde;o events in the tropical Pacific Ocean. During La Ni & ntilde;a, ocean CO2 emissions to the atmosphere increase abnormally (0.1-0.2 PgC/yr), which lasts about 3 years with a broader poleward extension (15 degrees S-15 degrees N). During El Ni & ntilde;o, ocean CO2 emissions to the atmosphere decrease abnormally (0.2-0.4 PgC/yr), which is more intense and lasts about 1 year with a narrower poleward extension (10 degrees S-10 degrees N). What's more, the ocean carbon anomalies caused by La Ni & ntilde;a tend to be more westward than those caused by El Ni & ntilde;o. Our study shows that this is due to the combination of asymmetries in wind, rainfall, circulation anomalies, and biological processes. This study will help people understand the ocean carbon sink deeply and improve the accuracy of carbon budget estimation
Presentation of the Citizens’ Observatory Pilots
No full textThe AGEO project aims to implement five pilots of citizen observatories to improve the monitoring and management of natural hazards in the Atlantic Arc Area, through active participation of stakeholders, local communities and citizens in multiple aspects of risk assessment and prevention. These will be referred to as “pilots” in the following
A practical framework to evaluate the feasibility of incentive-based approaches to reduce bycatch of marine mammals and other protected species
No full textFisheries bycatch is one of the biggest threats to marine mammal populations and an important conservation and management problem worldwide. Conventional marine mammal bycatch mitigation approaches typically rely on top-down, command-and-control regulations that often fail to create desired incentives for fishers to avoid bycatch. There is growing recognition of the need to explore alternative approaches that encourage behavioral change through the creation of an appropriate set of incentives – both economic and social – towards bycatch reduction. This study introduces a practical framework that aims to evaluate a range of dimensions related to the feasibility and durability of incentive-based approaches to mitigate marine mammal bycatch. We use this framework to examine seven case studies where incentive-based measures have been implemented or proposed, demonstrating both its applicability in a variety of contexts and usefulness in ex-ante assessment of alternative bycatch mitigation options. Our analysis underscores important operational aspects to consider in implementing such approaches, including the need for fine-scale data collection, the importance of a credible threat such as a fishery closure or loss of market access, the involvement of fishers in solution development, and the pivotal role of collective organizations in addressing marine mammal bycatch issues which almost always are complex and multi-faceted
Restricted feeding of goats during the last third of gestation and trans-generational effects on plasma progesterone in their female offspring
No full textFeeding levels can vary in goat farms for several reasons. Underfeeding of gestating dairy goats can occur and may influence fetal follicle development and future reproductive performance in their offspring. The objective of this experiment was to study the effect of restricted feeding during the last third of gestation on some reproductive parameters in female offspring (F1). Two feeding groups were formed using 60 Alpine and Saanen dairy goats to produce the F1 female offspring. The control group (C, n = 30) was fed to requirements. The restricted group (R, n = 30) was given the same diet, but the quantity corresponded to 50% of the amount given to the C group between -8 and -4 weeks, 60% between -5 and -4 weeks, 70% between -4 and -3 weeks and 80% from -2 weeks to parturition. Estrus was synchronized at 7 months of age in female F1 goats born to C (n = 17) or born to R goats (n = 15) with a progestagen-impregnated sponge and prostaglandin F2 alpha and eCG injections, and the goats were inseminated. Serial blood samples were collected over this period. After mating, plasma progesterone rose more slowly to reach a maximum plateau concentration in females born to R goats compared to females born to C goats (P 0.05), length of gestation (C, 151 +/- 2 days vs. R, 151 +/- 2 days) and kid mortality rate (mummified fetuses, stillbirth or death in first 48h) between the groups. However, birth weight was lower in R kids compared to C kids (4.0 +/- 0.11 kg vs. 4.5 +/- 0.10 kg, P = 0.007). In conclusion, maternal feed restriction during late pregnancy modified progesterone patterns after insemination in female offspring, although there was no effect on reproductive success
Unraveling Major Questions in Micronekton Ecology and Their Role in the Biological Carbon Pump Through Integrative Approaches and Autonomous Monitoring
No full textMicronekton consist of crustaceans, cephalopods, gelatinous organisms, and fishes that are 2–20 cm in size (Figure 1). These organisms have unique functional traits that impact their vertical migration patterns and ecosystem processes (Aparecido et al., 2023). Our understanding of their potential carbon transport and sequestration from the epipelagic (upper 200 m) to mesopelagic zones (200–1,000 m) or deeper (e.g., Boyd et al., 2019; Le Moigne, 2019; Cavan et al., 2019) is limited by the tools traditionally used to assess their biomass, diversity, and varied migration patterns (e.g., Annasawmy et al., 2019, 2024; Barbin et al., 2024; Eduardo et al., 2024). These knowledge gaps are notable considering that micronekton are ubiquitous throughout the world ocean