Elsevier

Ecological Modelling

Volume 437, 1 December 2020, 109297
Ecological Modelling

A Dynamic Energy Budget simulation approach to investigate the eco-physiological factors behind the two-stanza growth of yellowfin tuna (Thunnus albacares)

https://doi.org/10.1016/j.ecolmodel.2020.109297Get rights and content

Highlights

  • The growth of Indian Ocean yellowfin tuna shows a unique two-stanza pattern.

  • A bioenergetic model was developed in the context of Dynamic Energy Budget theory.

  • Parameters were derived from fitting to data and body-size scaling relationships.

  • The model reproduced well the data collected from yellowfin tuna farming experiences.

  • Competition for food and ontogenetic changes in diet may explain the growth pattern.

Abstract

The growth of yellowfin tuna has been the subject of considerable research efforts since the early 1960s. Most studies support a complex two-stanza growth pattern with a sharp acceleration departing from the von Bertalanffy growth curve used for most fish populations. This growth pattern has been assumed to result from a combination of physiological, ecological and behavioral factors but the role and contribution of each of them have not been addressed yet. We developed a bioenergetic model for yellowfin tuna in the context of Dynamic Energy Budget theory to mechanistically represent the processes governing yellowfin tuna growth. Most parameters of the model were inferred from Pacific bluefin tuna using body-size scaling relationships while some essential parameters were estimated from biological data sets collected in the Indian Ocean. The model proved particularly suitable for reproducing the data collected during the Pacific yellowfin tuna farming experience conducted by the Inter-American Tropical Tuna Commission at the Achotines Laboratory in Panama. In addition, model predictions appeared in agreement with knowledge of the biology and ecology of wild yellowfin tuna. We used our model to explore through simulations two major assumptions that might explain the existence of growth stanzas observed in wild yellowfin tuna: (i) a lower food supply during juvenile stage in relation with high intra- and inter-species competition and (ii) ontogenetic changes in food diet. Our results show that both assumptions are plausible although none of them is self-sufficient to explain the intensity of growth acceleration observed in wild Indian Ocean yellowfin tuna, suggesting that the two factors may act in concert. Our study shows that the yellowfin growth pattern is likely due to behavioral changes triggered by the acquisition of physiological abilities and anatomical traits through ontogeny that result in a major change in intensity of schooling and in a shift in the biotic habitat and trophic ecology of this commercially important tuna species.

Introduction

Yellowfin tuna (Thunnus albacares; YFT) is an epipelagic species widely distributed in the tropical and subtropical waters of the world’s major oceans (Pecoraro et al., 2017). Owing to its high value as food source, YFT supports important commercial and recreational fisheries. With an annual global catch of about 1.3 million tonnes in the last decade, it ranks among the world’s ten most harvested marine species (FAO, 2018). At global scale, YFT has recently been assessed as Near Threatened following the Red list criteria of the International Union for Conservation of Nature (Collette et al., 2001), while the assessments of the status of its four oceanic stocks conducted within the tuna Regional Fisheries Management Organizations indicate that overfishing currently occurs in the Indian Ocean (IOTC, 2018).

For assessment and management purpose, growth of wild YFT has been the subject of considerable research efforts since the 1960s through analysis of mark-recapture data, size frequency distribution of commercial fishery catches and ageing from calcified and bony structures (Diaz, 1963, Schaefer, Chatwin, Broadhead, 1961, Wild, Foreman, 1980). YFT growth varies between ocean basins and regions and shows in some areas some complex pattern that departs from the traditional von Bertalanffy growth curve used for most fish stocks (Pecoraro et al., 2017). In particular, some growth studies conducted in the Atlantic, Indian and Western-Central Pacific Oceans support a two-stanza growth pattern with a sharp acceleration in growth rate at about 60–65 cm fork length (Dortel, Sardenne, Bousquet, Rivot, Million, Le Croizier, Chassot, 2015, Eveson, Million, Sardenne, Le Croizier, 2015, Gascuel, Fonteneau, Capisano, 1992, Lehodey, Leroy, 1999).

The complex growth pattern observed in some populations of YFT has been assumed to result from a combination of physiological, ecological and behavioral factors but the role and contribution of each of them have not been addressed yet (Bard, 1984, Dortel, Sardenne, Bousquet, Rivot, Million, Le Croizier, Chassot, 2015, Fonteneau, 1980, Gaertner, Pagavino, 1992). A better understanding of these mechanisms is essential to assess the plasticity of YFT growth and eventually strengthen the scientific advice on the stock status and improve the overall quality of current stock assessments.

We investigated the factors governing the growth of YFT with a bioenergetic model that covers the different post-metamorphic life stages of the Indian Ocean YFT within the framework of the Dynamic Energy Budget (DEB) theory (Kooijman, 2010). DEB theory has already proven successful to study growth and reproduction of a large range of marine taxa (Freitas, Cardoso, Lika, Peck, Campos, Kooijman, van der Veer, 2010, Pecquerie, Petitgas, Kooijman, 2009, Sousa Tnia, Domingos Tiago, Kooijman S.A.L.M, 2008, van der Veer, Cardoso, van der Meer, 2006) and more recently to study the dynamics of populations and ecosystems (Maury, 2017, Maury, Poggiale, 2013, Pethybridge, Roos, Loizeau, Pecquerie, Bacher, 2013). Other bioenergetic approaches are available but they are generally specific to a particular life stage and unsuitable for modelling the changes between distinct life stages (Hansen, Boisclair, Brandt, Hewett, Kitchell, Lucas, Ney, 1993, Ney, 1993). In contrast, the DEB theory provides a powerful conceptual framework to describe the lifelong growth in relation to other physiological requirements, such as metabolism and body internal maintenance, development and reproduction, as a function of environmental food conditions and organism state (Freitas, Cardoso, Lika, Peck, Campos, Kooijman, van der Veer, 2010, Kooijman, 2010).

Section snippets

Data sources

We collected data sets from the literature for both wild and farmed YFT to compare the outputs of the bioenergetic model with morphometric, ageing and reproduction observations.

Validation of a reference DEB model for yellowfin tuna

The reference DEB model successfully reproduced the growth in length and the length-weight relationship observed for farmed Pacific YFT as described in the study of Wexler et al. (2003). Furthermore, the observed values of FDR and FCR were well within the simulated range (Fig. 2). Thus, the set of parameters, some of which were derived from PBT (Jusup et al., 2011), appeared suitable to assess the effects of variations in the quantity and quality of food on YFT growth (Table 1).

From the

Discussion

We formulated a bioenergetic model covering the juvenile and adult stages of YFT in the context of Dynamic Energy Budget theory. Some essential parameters of the model were estimated with Bayesian analysis from morphometric, age, and reproduction data sets collected from YFT sampled in the Indian Ocean while other parameters were derived from the DEB model developed for PBT (Jusup et al., 2011). Our results show that both lower food availability in the juvenile stage and ontogenetic changes in

Conclusion & perspectives

Building on the Dynamic Energy Budget modelling framework that mechanistically links the biology of individual organisms to abiotic drivers (Kooijman, 2010), our model suggests that the unique growth pattern observed in wild YFT could stem from a major change in intensity of schooling and associative behavior with size, which would substantially modify both the quantity and quality of food available for maintenance, reproduction and growth. This change would be triggered by the acquisition of

Declaration of Competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This study was funded by the Data Collection Framework of the European Union (Reg.199/2008, 665/2008 and SI2.604453), the French Ministry of Agriculture and Fisheries (301629/00), ORTHONGEL, the Institut de Recherche pour le Developpement, and the French ANR funded project EMOTION (ANR 11JSV7 007 01). We wish to acknowledge the contributions of all the people who have been involved in the Regional Tuna Tagging Project of the Indian Ocean, funded under the 9th European Development Fund

References (80)

  • L. Pecquerie et al.

    Analyzing variations in life-history traits of Pacific salmon in the context of Dynamic Energy Budget (DEB) theory

    J. Sea Res.

    (2011)
  • L. Pecquerie et al.

    Modeling fish growth and reproduction in the context of the Dynamic Energy Budget theory to predict environmental impact on anchovy spawning duration

    J. Sea Res.

    (2009)
  • H. Pethybridge et al.

    Responses of European anchovy vital rates and population growth to environmental fluctuations: an individual-based modeling approach

    Ecol. Modell.

    (2013)
  • M. Potier et al.

    Forage fauna in the diet of three large pelagic fishes (lancetfish, swordfish and yellowfin tuna) in the western equatorial Indian Ocean

    Fish. Res.

    (2007)
  • F. Sardenne et al.

    Determining the age of tropical tunas in the Indian Ocean from otolith microstructures

    Fish. Res.

    (2015)
  • K.M. Schaefer et al.

    Movements, behavior, and habitat utilization of yellowfin tuna (Thunnus albacares) in the Pacific ocean off Baja California, Mexico, determined from archival tag data analyses, including unscented kalman filtering

    Fish. Res.

    (2011)
  • M. Schaefer et al.

    Tagging and recovery of tropical tunas

    Technical report

    (1961)
  • L. Tremblay-Boyer et al.

    Stock assessment of yellowfin tuna in the western and central Pacific Ocean

    Thirteenth Regular Session of the Scientific Committee

    (2017)
  • J.B. Wexler et al.

    Temperature and dissolved oxygen requirements for survival of yellowfin tuna, Thunnus albacares, larvae

    J. Exp. Mar. Biol. Ecol.

    (2011)
  • J.B. Wexler et al.

    Tank culture of yellowfin tuna, Thunnus albacares: developing a spawning population for research purposes

    Aquaculture

    (2003)
  • A. Wild et al.

    The relationship between otolith increments and time for yellowfin and skipjack tuna marked with tetracycline

    Inter-Am. Tropic. Tuna Commission Bull.

    (1980)
  • Anonymous

    West sumatera tuna tagging project 2006–2007, Final Report

    Technical Report

    (2008)
  • F. Bard

    Croissance de l’albacore (Thunnus albacares) atlantique d’après les données des marquages

    Collect. Vol. Sci. Papers ICCAT

    (1984)
  • J.M. Blank et al.

    Influence of swimming speed on metabolic rates of juvenile Pacific bluefin tuna and yellowfin tuna

    Physiol. Biochem. Zool.

    (2007)
  • N. Bodin et al.

    Ecological data for western Indian Ocean tuna

    Ecology

    (2018)
  • R.W. Brill

    A review of temperature and oxygen tolerance studies of tunas pertinent to fisheries oceanography, movement models and stock assessments

    Fish. Oceanogr.

    (1994)
  • Couture-Beil, A., Schnute, J., Haigh, R., 2010. PBSddesolve: solver for delay differential equations. rpackage version...
  • H. Dewar et al.

    Studies of tropical tuna swimming performance in a large water tunnel - energetics

    J. Exp. Biol.

    (1994)
  • E. Diaz

    An increment technique for estimating growth parameters of tropical tunas, as applied to yellowfin tuna (Thunnus albacares)

    Inter-Am. Tropic. Tuna Commission Bull.

    (1963)
  • E. Dortel et al.

    Accounting for age uncertainty in growth modeling, the case study of yellowfin tuna Thunnus albacares of the Indian Ocean

    PLoS ONE

    (2013)
  • S. Dueri et al.

    Application of the APECOSM-E model to the skipjack tuna (Katsuwonus pelamis) fisheries of the Indian Ocean

    IOTC Proceedings

    (2010)
  • J. Eveson et al.

    Estimating growth of tropical tunas in the Indian Ocean using tag-recapture data and otolith based age estimates

    Fish. Res.

    (2015)
  • FAO

    The state of world fisheries and aquaculture

    Technical report

    (2018)
  • J. Farley et al.

    Progress on yellowfin tuna age and growth in the WCPO (Project 82)

    Fifteenth Regular Session of the Scientific Committee

    (2019)
  • J. Farley et al.

    Progress on yellowfin tuna age and growth in the WCPO. WCPFC Project 82

    Fourteenth Regular Session of the Scientific Committee

    (2018)
  • A. Fonteneau

    Croissance de l’albacore (Thunnus albacares) de l’Atlantique Est

    Collect. Vol. Sci. Paper. ICCAT

    (1980)
  • A. Fonteneau et al.

    An overview of yellowfin tuna growth in the Atlantic ocean: Von Bertalanffy or multistanza growth?

    ICCAT Col. Vol. Sci. Pap.

    (2013)
  • A. Fonteneau et al.

    Global spatio-temporal patterns in tropical tuna purse seine fisheries on drifting fish aggregating devices (DFADs): taking a historical perspective to inform current challenges

    Aquat. Living Resour.

    (2013)
  • V. Freitas et al.

    Temperature tolerance and energetics: a dynamic energy budget-based comparison of north Atlantic marine species

    Philos. Trans. R. Soc. B

    (2010)
  • D. Gaertner et al.

    Observations sur la croissance de l’albacore (Thunnus albacares) dans l’Atlantique Ouest

    Collect. Vol. Sci. Paper. ICCAT

    (1992)
  • Cited by (0)

    View full text