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Abadie, E., Muguet, A., Berteaux, T., Chomérat, N., Hess, P., ROQUE D'ORBCASTEL, E., et al. (2016). Toxin and Growth Responses of the Neurotoxic Dinoflagellate Vulcanodinium rugosum to Varying Temperature and Salinity. Toxins, 8(5), 136.
Résumé: Vulcanodinium rugosum, a recently described species, produces pinnatoxins. The IFR-VRU-01 strain, isolated from a French Mediterranean lagoon in 2010 and identified as the causative dinoflagellate contaminating mussels in the Ingril Lagoon (French Mediterranean) with pinnatoxin-G, was grown in an enriched natural seawater medium. We tested the effect of temperature and salinity on growth, pinnatoxin-G production and chlorophyll a levels of this dinoflagellate. These factors were tested in combinations of five temperatures (15, 20, 25, 30 and 35 °C) and five salinities (20, 25, 30, 35 and 40) at an irradiance of 100 µmol photon m−2 s−1. V. rugosum can grow at temperatures and salinities ranging from 20 °C to 30 °C and 20 to 40, respectively. The optimal combination for growth (0.39 ± 0.11 d−1) was a temperature of 25 °C and a salinity of 40. Results suggest that V. rugosum is euryhaline and thermophile which could explain why this dinoflagellate develops in situ only from June to September. V. rugosum growth rate and pinnatoxin-G production were highest at temperatures ranging between 25 and 30 °C. This suggests that the dinoflagellate may give rise to extensive blooms in the coming decades caused by the climate change-related increases in temperature expected in the Mediterranean coasts.
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Anastasiadi, D., Vandeputte, M., Sánchez-Baizán, N., Allal, F., & Piferrer, F. (2018). Dynamic epimarks in sex-related genes predict gonad phenotype in the European sea bass, a fish with mixed genetic and environmental sex determination. Epigenetics, 13(9), 988–1011.
Résumé: The integration of genomic and environmental influences into methylation patterns to bring about a phenotype is of central interest in developmental epigenetics, but many details are still unclear. The sex ratios of the species used here, the European sea bass, are determined by genetic and temperature influences. We created four families from parents known to produce offspring with different sex ratios, exposed larvae to masculinizing temperatures and examined, in juvenile gonads, the DNA methylation of seven genes related to sexual development by a targeted sequencing approach. The genes most affected by both genetics and environment were cyp19a1a and dmrt1, with contrasting sex-specific methylation and temperature responses. The relationship between cyp19a1a methylation and expression is relevant to the epigenetic regulation of vertebrate sex, and we report the evidence of such relationship only below a methylation threshold, 80%, and that it was sex-specific: negatively correlated in females but positively correlated in males. From parents to offspring, the methylation in gonads was midway between oocytes and sperm, with bias towards oocytes for amh-r2, er-β2, fsh-r and cyp19a1a. In contrast, dmrt1 levels resembled those of sperm. The methylation of individual CpGs from foxl2, er-β2 and nr3c1 were conserved from parents to offspring, whereas those of cyp19a1a, dmrt1 and amh-r2 were affected by temperature. Utilizing a machine-learning procedure based on the methylation levels of a selected set of CpGs, we present the first, to our knowledge, system based on epigenetic marks capable of predicting sex in an animal with 90% accuracy and discuss possible applications.
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Andrello, M., de Villemereuil, P., Carboni, M., Busson, D., Fortin, M. - J., Gaggiotti, O. E., et al. (2020). Accounting for stochasticity in demographic compensation along the elevational range of an alpine plant. Ecol. Lett., .
Résumé: Demographic compensation arises when vital rates change in opposite directions across populations, buffering the variation in population growth rates, and is a mechanism often invoked to explain the stability of species geographic ranges. However, studies on demographic compensation have disregarded the effects of temporal variation in vital rates and their temporal correlations, despite theoretical evidence that stochastic dynamics can affect population persistence in temporally varying environments. We carried out a seven-year-long demographic study on the perennial plant Arabis alpina (L.) across six populations encompassing most of its elevational range. We discovered demographic compensation in the form of negative correlations between the means of plant vital rates, but also between their temporal coefficients of variation, correlations and elasticities. Even if their contribution to demographic compensation was small, this highlights a previously overlooked, but potentially important, role of stochastic processes in stabilising population dynamics at range margins.
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Bach, P., Gaertner, D., Menkes, C., Romanov, E., & Travassos, P. (2009). Effects of the gear deployment strategy and current shear on pelagic longline shoaling. Fish Res., 95, 55–64.
Résumé: Historical longline catch per unit effort (CPUE) constitutes the major time series used in tuna stock assessment to followthe trend in abundance since the beginning of the large-scale tuna fisheries. The efficiency and species composition of a longline fishing operations essentially depends on the overlap in the vertical and spatial distribution between hooks and species habitat. Longline catchability depends on the vertical distribution of hooks and the aim of our paper was to analyse principal factors affecting the deviation of observed longline hook depths from predicted values. Since observed hook depth is usually shallower than predicted, this deviation is called longline shoaling.We evaluate the accuracy of hook depth distribution estimated from a theoretical catenary model commonly used in longline CPUE standardizations. Temperature-depth recorders (TDRs) were deployed on baskets of a monitored longline. Mainline shapes and maximum fishing depths were similar to gear configurations commonly used to target both yellowfin and bigeye tuna by commercial longliners in the central part of the South Pacific Ocean. Our working hypothesis assumes that the maximum fishing depth reached by the mainline depends on the gear configuration (sag ratio, mainline length per basket), the fishing tactics (bearing of the setting) and environmental variables characterizing water mass dynamics (wind stress, current velocity and shear). Based on generalized additive models (GAMs) simple transformations are proposed to account for the non-linearity between the shoaling and explanatory variables. Then, generalized linear models (GLMs) were fit to model the effects of explanatory variables on the longline shoaling. Results indicated that the shoaling (absolute aswell as relative) was significantly influenced by (1) the shape of the mainline (i.e., the tangential angle), which is the strongest predictor, and (2) the current shear and the direction of setting. Geometric forcing (i.e. transverse versus in-line) between the environment and the longline set is shown for the first time from in situ experimental fishing data. Results suggest that a catenary model that does not take these factors into consideration provides a biased estimate of the vertical distribution of hooks and must be used with caution in CPUEs standardization methods. Since catchability varies in time and space we discuss how suitable data could be routinely collected onboard commercial fishing vessels in order to estimate longline catchability for stock assessments.
© 2008 Elsevier B.V. All rights reserved.. |
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Baidai, Y., Dagorn, L., Amande, M. J., Gaertner, D., & Capello, M. (2020). Machine learning for characterizing tropical tuna aggregations under Drifting Fish Aggregating Devices (DFADs) from commercial echosounder buoys data. Fish Res., 229, 105613.
Résumé: The use of echosounder buoys deployed in conjunction with Drifting Fish Aggregating Devices (DFADs) has progressively increased in the tropical tuna purse seine fishery since 2010 as a means of improving fishing efficiency. Given the broad distribution of DFADs, the acoustic data provided by echosounder buoys can provide an alternative to the conventional CPUE index for deriving trends on tropical tuna stocks. This study aims to derive reliable indices of presence of tunas (and abundance) using echosounder buoy data. A novel methodology is presented which utilizes random forest classification to translate the acoustic backscatter from the buoys into metrics of tuna presence and abundance. Training datasets were constructed by cross-referencing acoustic data with logbook and observer data which reported activities on DFADs (tuna catches, new deployments and visits of DFADs) in the Atlantic and Indian Oceans from 2013 to 2018. The analysis showed accuracies of 75 and 85 % for the recognition of the presence/absence of tuna aggregations under DFADs in the Atlantic and Indian Oceans, respectively. The acoustic data recorded at ocean-specific depths (6-45m in the Atlantic and 30-150m in the Indian Ocean) and periods (4 a.m.-4 p.m.) were identified by the algorithm as the most important explanatory variables for detecting the presence of tuna. The classification of size categories of tuna aggregations showed a global accuracy of nearly 50 % for both oceans. This study constitutes a milestone towards the use of echosounder buoys data for scientific purposes, including the development of promising fisheries-independent indices of abundance for tropical tunas.
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