1
|
Teichert N, Tabouret H, Lizé A, Daverat F, Acou A, Trancart T, Virag LS, Pécheyran C, Feunteun E, Carpentier A. Quantifying larval dispersal portfolio in seabass nurseries using otolith chemical signatures. MARINE ENVIRONMENTAL RESEARCH 2024; 196:106426. [PMID: 38442591 DOI: 10.1016/j.marenvres.2024.106426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 02/26/2024] [Accepted: 02/26/2024] [Indexed: 03/07/2024]
Abstract
The temporal asynchronies in larvae production from different spawning areas are fundamental components for ensuring stability and resilience of marine metapopulations. Such a concept, named portfolio effect, supposes that diversifying larval dispersal histories should minimize the risk of recruitment failure by increasing the probability that at least some larvae successfully settle in nursery. Here, we used a reconstructive approach based on otolith chemistry to quantify the larval dispersal portfolio of the European seabass, Dicentrarchus labrax, across six estuarine nursery areas of the northeast Atlantic Ocean. The analysis of natal and trajectory signatures indicated that larvae hatch in distinct environments and then dispersed in water masses featured by contrasting chemical signatures. While some trace elements appeared affected by temporal changes (Mn and Sr), others varied spatially during the larval stage but remained poorly affected by temporal fluctuation and fish physiology (Ba, Cu, Rb and Zn). We then proposed two diversity metrics based on richness and variations of chemical signatures among populations to reflect spatio-temporal diversity in natal origins and larval trajectories (i.e., estimates of dispersal portfolio). Along the French coast, the diversity estimates were maximum in nurseries located at proximity of offshore spawning sites and featured by complex offshore hydrodynamic contexts, such as the Mont St-Michel bay. Finally, our findings indicate that the dispersal portfolio was positively related with the local abundance of seabass juveniles, supporting the assumption that heterogeneity in dispersal history contributes to promote recruitment success in nurseries.
Collapse
Affiliation(s)
- Nils Teichert
- UMR 8067 BOREA (MNHN, CNRS, IRD, SU, UCN, UA), Laboratoire de Biologie des Organismes et Ecosystèmes Aquatiques, Paris, France; MNHN, Station Marine de Dinard, CRESCO, 35800, Dinard, France.
| | - Hélène Tabouret
- Université de Pau et des Pays de l'Adour, E2S UPPA, CNRS, IPREM, Pau, France
| | - Anne Lizé
- UMR 8067 BOREA (MNHN, CNRS, IRD, SU, UCN, UA), Laboratoire de Biologie des Organismes et Ecosystèmes Aquatiques, Paris, France; MNHN, Station Marine de Dinard, CRESCO, 35800, Dinard, France; School of Life Sciences, University of Liverpool, L697ZB, Liverpool, UK
| | | | - Anthony Acou
- Centre d'expertise et de données PatriNat (OFB-MNHN-CNRS-IRD), Station marine de Dinard, CRESCO, 35800, Dinard, France; Pôle R&D OFB, INRAE, Institut Agro -UPPA MIAME (MIgrateurs AMphihalins dans leur Environnement), 35000, Rennes, France
| | - Thomas Trancart
- UMR 8067 BOREA (MNHN, CNRS, IRD, SU, UCN, UA), Laboratoire de Biologie des Organismes et Ecosystèmes Aquatiques, Paris, France; MNHN, Station Marine de Dinard, CRESCO, 35800, Dinard, France
| | | | | | - Eric Feunteun
- UMR 8067 BOREA (MNHN, CNRS, IRD, SU, UCN, UA), Laboratoire de Biologie des Organismes et Ecosystèmes Aquatiques, Paris, France; MNHN, Station Marine de Dinard, CRESCO, 35800, Dinard, France; CGEL, EPHE-PSL, 35800, Dinard, France
| | - Alexandre Carpentier
- Université de Rennes, UMR 8067 BOREA (MNHN, CNRS, IRD, SU, UCN, UA) Laboratoire de Biologie des Organismes et Ecosystèmes Aquatiques, Rennes, France
| |
Collapse
|
2
|
Wang W, Huang J, Hu Y, Feng J, Gao D, Fang W, Xu M, Ma C, Fu Z, Chen Q, Liang X, Lu J. Seascapes Shaped the Local Adaptation and Population Structure of South China Coast Yellowfin Seabream (Acanthopagrus latus). MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2024; 26:60-73. [PMID: 38147145 DOI: 10.1007/s10126-023-10277-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 12/14/2023] [Indexed: 12/27/2023]
Abstract
Understanding the genetic composition and regional adaptation of marine species under environmental heterogeneity and fishing pressure is crucial for responsible management. In order to understand the genetic diversity and adaptability of yellowfin seabream (Acanthopagrus latus) along southern China coast, this study was conducted a seascape genome analysis on yellowfin seabream from the ecologically diverse coast, spanning over 1600 km. A total of 92 yellowfin seabream individuals from 15 sites were performed whole-genome resequencing, and 4,383,564 high-quality single nucleotide polymorphisms (SNPs) were called. By conducting a genotype-environment association analysis, 29,951 adaptive and 4,328,299 neutral SNPs were identified. The yellowfin seabream exhibited two distinct population structures, despite high gene flow between sites. The seascape genome analysis revealed that genetic structure was influenced by a variety of factors including salinity gradients, habitat distance, and ocean currents. The frequency of allelic variation at the candidate loci changed with the salinity gradient. Annotation of these loci revealed that most of the genes are associated with osmoregulation, such as kcnab2a, kcnk5a, and slc47a1. These genes are significantly enriched in pathways associated with ion transport including G protein-coupled receptor activity, transmembrane signaling receptor activity, and transporter activity. Overall, our findings provide insights into how seascape heterogeneity affects adaptive evolution, while providing important information for regional management in yellowfin seabream populations.
Collapse
Affiliation(s)
- Wenhao Wang
- School of Marine Sciences, Sun Yat-sen University, Zhuhai, China
| | - Junrou Huang
- School of Marine Sciences, Sun Yat-sen University, Zhuhai, China
| | - Yan Hu
- School of Marine Sciences, Sun Yat-sen University, Zhuhai, China
| | - Jianxiang Feng
- School of Marine Sciences, Sun Yat-sen University, Zhuhai, China
- Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
| | - Dong Gao
- School of Marine Sciences, Sun Yat-sen University, Zhuhai, China
| | - Wenyu Fang
- School of Marine Sciences, Sun Yat-sen University, Zhuhai, China
| | - Meng Xu
- School of Marine Sciences, Sun Yat-sen University, Zhuhai, China
| | - Chunlei Ma
- School of Marine Sciences, Sun Yat-sen University, Zhuhai, China
| | - Zhenqiang Fu
- School of Marine Sciences, Sun Yat-sen University, Zhuhai, China
| | - Qinglong Chen
- School of Marine Sciences, Sun Yat-sen University, Zhuhai, China
| | - Xuanguang Liang
- School of Marine Sciences, Sun Yat-sen University, Zhuhai, China
| | - Jianguo Lu
- School of Marine Sciences, Sun Yat-sen University, Zhuhai, China.
- Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China.
- Guangdong Provincial Key Laboratory of Marine Resources and Coastal Engineering, Guangzhou, Guangdong, China.
- Pearl River Estuary Marine Ecosystem Research Station, Ministry of Education, Zhuhai, China.
| |
Collapse
|