Pelagic habitat and offspring survival in the eastern stock of Atlantic bluefin tuna
Open accessAbstract
In this manuscript, we test how an understanding of geographical variation in larval fitness in relation to temperature and habitat use could be a useful method to improve our understanding of recruitment and develop better indices of annual recruitment. On the basis of the assumption that growth and survival of tuna larvae are influenced by temperature, we have developed a potential larval survival index for Atlantic bluefin tuna (Thunnus thynnus) by combining empirical data from egg and larval rearing experiments with temperature data from hydrodynamic models. The experiments were designed to test the full range of temperature variability that bluefin larvae would experience in the field and provide a mechanistic understanding of the processes driving egg and larval survival. We then developed a biological model using the temperature-related growth expressions and a size-dependent survival function for the larvae. The biological model was applied to a time-series of spatially explicit temperature data for the western Mediterranean from the Strait of Gibraltar to 6°E, which includes the major recognized bluefin tuna eastern stock spawning area, the Balearic Sea. Our results show that areas with high probabilities of larval survival coincide with those that would be considered as optimal based on other data sources (ichthyoplankton surveys, spawning female locations from commercial fisheries data, and adult tracking data). However, evidence of spawning has been found in areas with suboptimal thermal habitats, as predicted by the model, which we discuss regarding sampling effort and salinity fronts. There was a good match between the survival index and recruitment indices from standardized CPUE fisheries data. These results have implications for our understanding of the recruitment process of the eastern stock of Atlantic bluefin tuna, since they suggest that the combined effects of temporal and spatial variability of the environment drive recruitment success, which has important implications for the management of the species.
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Written from the paper’s full text.
TL;DR
The authors built a temperature-driven potential larval survival index for eastern Atlantic bluefin tuna by combining laboratory egg/larval rearing experiments with hydrodynamic model temperature fields for the western Mediterranean (2000–2014). High-survival areas matched independent evidence of optimal spawning habitat, and the index tracked recruitment indices from standardized CPUE data, though spawning was also recorded in thermally suboptimal areas.
Key findings
- Areas with high modelled probabilities of larval survival coincided with areas identified as optimal from other data sources: ichthyoplankton surveys, spawning female locations from commercial fisheries data, and adult tracking data.
- Evidence of spawning was nonetheless found in areas with suboptimal thermal habitats as predicted by the model; the authors discuss this in relation to sampling effort and salinity fronts.
- There was a good match between the survival index and recruitment indices derived from standardized CPUE fisheries data.
- The authors conclude that combined temporal and spatial environmental variability drives recruitment success, with implications for management of the eastern stock.
Methods
- Laboratory egg and larval rearing experiments were designed to span the full range of temperature variability bluefin larvae would experience in the field, providing temperature-related growth expressions and a size-dependent larval survival function; these were combined into a biological model producing a potential larval survival index.
- The model was applied to a spatially explicit temperature time-series for the western Mediterranean from the Strait of Gibraltar to 6°E (including the Balearic Sea spawning area) for 2000–2014, the years with detailed monitoring of larval, spawner, and tracking data.
- Environmental data selection was validated against 72 CTD observations from summer 2004 across four oceanographic models; CMEMS-MED versions best replicated temperature (correlation near 0.9, centred RMSD around 0.4), whereas salinity was poorly represented (correlations around 0.4) and dynamic height poorly represented (all models below 0.35 except MEDAR-MEDATLAS at 0.65), so only CMEMS-MED temperature was used. Egg release probability was estimated by fitting a polynomial to the gonadosomatic index of 528 females sampled from the commercial fishery (Strait of Gibraltar to Balearic Sea, spring–summer 2003–2014), with daily release probabilities normalized to sum to 1 per spawning season.
Limitations
- Stated in the paper: model salinity was not well represented (correlations around 0.4), so frontal locations could not be computed from models and field cruise salinity maps were used instead; dynamic height of mesoscale structures was also poorly represented, making model-derived geostrophic currents unusable for drift calculations; spawning in suboptimal thermal habitats is discussed with respect to sampling effort and salinity fronts.
- Stated assumptions: the same spawning window applies to all years, and the duration of an individual fish's spawning period is independent of body size.
- Evident from the text provided: only pages 1–3 of 10 were available (abstract, introduction, and methods), so the results and discussion sections could not be checked and the quantitative outcomes reported here rest on the abstract alone.
Model-written summary. Check it against the paper before relying on it.
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Cites
Statistics
Claims the paper makes
1 of 1 cited sources checked · 0 supported · 0 flagged · accuracy not yet measured
- Findingnone given§ Abstract
There was a good match between the survival index and recruitment indices from standardized CPUE fisheries data.
“There was a good match between the survival index and recruitment indices from standardized CPUE fisheries data.”
Quote in the paperSubstantial claim - Findingreasoning§ Introduction
Only temperature data were well represented by the available models for the period 2000-2014.
“As such, only temperature data were well represented by the available models for the period of study (2000–2014) and, therefore, only the temperature model from CMEMS-MED was used.”
Quote in the paperSubstantial claim - Findingreasoning§ Abstract
Evidence of spawning has been found in areas with suboptimal thermal habitats, as predicted by the model.
“However, evidence of spawning has been found in areas with suboptimal thermal habitats, as predicted by the model, which we discuss regarding sampling effort and salinity fronts.”
Quote in the paperSubstantial claim - Findingown data§ Introduction
The CMEMS-MED model replicates very well the interannual variability of temperature in the area centred on the Balearic Islands.
“This comparison shows that the CMEMS-MED model replicates very well the interannual variability of temperature in the area (Supplementary Figure S3).”
Quote in the paperSubstantial claim - Findingown data§ Abstract
Areas with high probabilities of larval survival coincide with those that would be considered optimal based on other data sources (ichthyoplankton surveys, spawning female locations from commercial fisheries data, and adult tracking data).
“Our results show that areas with high probabilities of larval survival coincide with those that would be considered as optimal based on other data sources (ichthyoplankton surveys, spawning female locations from commercial fisheries data, and adult tracking data).”
Quote in the paperSubstantial claim
- Interpretationreasoning§ Abstract
The combined effects of temporal and spatial variability of the environment drive recruitment success of the eastern stock of Atlantic bluefin tuna.
“These results have implications for our understanding of the recruitment process of the eastern stock of Atlantic bluefin tuna, since they suggest that the combined effects of temporal and spatial variability of the environment drive recruitment success”
Quote in the paperSubstantial claim
- Classified as probably not a substantial claim. 2
- May combine two claims. 2
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ IntroductionThe increasing trend in annual recruitment of eastern Atlantic bluefin tuna from the 1970s to the early 2000s has been related to increasing summer temperatures in the Balearic Sea.
“the increasing trend in annual recruitment from the 1970s to the early 2000s has been related to increasing summer temperatures in the Balearic Sea (Harford et al., 2017)”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Harford et al., 2017 source
The 'Detecting environmental effects on recruitment' section links July sea-surface temperature near Mediterranean spawning areas to eastern Atlantic bluefin tuna recruitment. But the paper does not establish that recruitment rose from the 1970s to the early 2000s because summer temperatures increased in the Balearic Sea. Its scenario analysis instead reports a state-dependent relationship, negative in 63% of Mediterranean predictions and positive in 37%. (LLM, conf=0.86)
Experimental — accuracy not yet measured
May combine two claims.
Findingown data§ IntroductionBoth CMEMS-MED model versions were the best at replicating the spatial pattern of the CTD temperature observations, with a correlation coefficient close to 0.9 and a centred Root-Mean-Square difference around 0.4.
“with a correlation coefficient close to 0.9 and a centred Root-Mean-Square difference around 0.4”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data§ IntroductionSalinity was not well represented in the models and could not be used for calculations of the location of frontal areas.
“Therefore, salinity was not well represented in the models and could not be used for calculations of the location of frontal areas.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Study design and conductnone given§ AbstractThe egg and larval rearing experiments were designed to test the full range of temperature variability that bluefin larvae would experience in the field.
“The experiments were designed to test the full range of temperature variability that bluefin larvae would experience in the field and provide a mechanistic understanding of the processes driving egg and larval survival.”
Quote in the paperSubstantial claim
The authors state this as an assumption.
Growth and survival of tuna larvae are influenced by temperature.
“On the basis of the assumption that growth and survival of tuna larvae are influenced by temperature”
The authors state this as an assumption.
The same spawning window applies to all years.
“We made two assumptions: (i) the same spawning window applies to all years”
The authors state this as an assumption.
The duration of an individual fish's spawning period is independent of the spawner's body size.
“and (ii) the duration of an individual fish’s spawning period is independent of the spawner’s body size.”
The paper relies on this without support.
Environmental information is rarely included in stock assessments of large pelagic fish.
“environmental information is rarely included in stock assessments of large pelagic fish”
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Musyl, M. K., McNaughton, L. M., Jia, Y., Humphreys, R. L., & Kramer, R. (2026) · Reviews in Fish Biology and Fisheries · doi:10.1007/s11160-026-10062-3
Kurt, T. T., Duman, G. S., & Mutlu, E. (2026) · Diversity · doi:10.3390/d18100583
Sánchez-Fabrés, E., Tugores, M. P., Carrasco, I. H., Ospina-Álvarez, A., Crespo, F. J. A., Sánchez-Leal, R., Mourre, B., & Álvarez-Berastegui, D. (2026) · Fisheries Oceanography · doi:10.1111/fog.70077
Self-citation
- Authors
- Reglero, P., Balbín, R., Abascal, F. J., Medina, A., Alvarez-Berastegui, D., Rasmuson, L., Mourre, B., Saber, S., Ortega, A., Blanco, E., de la Gándara, F., Alemany, F. J., Ingram, G. W., & Hidalgo, M.
- Affiliations
- Instituto Español de Oceanografía (ES)
- Centro Oceanográfico de Canarias, Instituto Español de Oceanografía, Santa Cruz de Tenerife, Spain
- Universidad de Cádiz (ES)
- Balearic Islands Coastal Observing and Forecasting System, Parc Bit, Naorte, Bloc A 28p. pta 3, Palma de Mallorca, Balearic Islands, Spain
- Marine Resources Program, Oregon Department of Fish and Wildlife, 2040 SE Marine Science Drive, Newport, OR, USA
- Instituto Español de Oceanografía, Centro Oceanográfico de Málaga, Puerto Pesquero, s/n, Fuengirola, Spain
- Instituto Español de Oceanografía, Centro Oceanográfico de Murcia, Puerto de Mazarrón, Murcia, Spain
- Instituto Español de Oceanografía, Centre Oceanogràfic de les Balears, Ecosystem Oceanography Group (GRECO), Moll de Ponent s/n, Palma de Mallorca, Spain
- NOAA, National Marine Fisheries Service, Southeast Fisheries Science Center, Mississippi Laboratories, 3209 Frederic Street, Pascagoula, MS, USA
- Corresponding author
- Reglero, Patricia
- Venue
- ICES Journal of Marine Science
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-10-04
- Volume
- 76
- Issue
- 2
- Pages
- 549-558
- ISSN
- 1054-3139 (ISSN-L)
- 1095-9289
- OpenAlex
- W2895067041
- Cited by
- 28
- References
- 34
- Citations by year
- 2026: 5 · 2025: 3 · 2024: 2 · 2023: 2 · 2022: 3 · 2021: 5 · 2020: 3 · 2019: 5
- FWCI
- 1.87
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- ICES Journal of Marine Science (publishedVersion)
- DIGITAL.CSIC (Spanish National Research Council (CSIC)) (publishedVersion, other-oa)
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Marine and fisheries research
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Fish Ecology and Management Studies
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Ichthyology and Marine Biology
- Keywords
- Thunnus thynnus, larval survival, recruitment (biology), pelagic habitat, thermal habitat, spawning grounds, Balearic Sea, Western Mediterranean, salinity front, stock assessment
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-16.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-16.
Cited sources are checked by gpt-6-sol.
Statistics and arithmetic are recomputed, not judged.
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