Early-life ontogenetic developments drive tuna ecology and evolution
Introduction
Understanding life-history traits of marine animals in terms of physiological constraints is fundamentally important for inferring their ecological function and role among species. Commercial tuna species have received particular attention in this context because of their unique life-history traits among teleosts and a captivating functional evolution, including large size, elevated body temperature, and exceptional swimming ability (e.g., Carey and Teal, 1966; Graham and Dickson, 2004). Despite sharing some general traits, tuna species differ between themselves in terms of body length, body mass, life span, and fecundity (e.g., Matsumoto et al., 1984; Santamaria et al., 2009). In peer-reviewed literature, for example, the maximum reported body length of skipjack tuna (SKJ; Katsuwonus pelamis) is only 94 cm (Matsumoto et al., 1984), while that of Pacific bluefin tuna (PBT; Thunnus orientalis) and Atlantic bluefin tuna (ABT; Thunnus thynnus) is 265 cm (Masuma, 2009) and 372 cm (Santamaria et al., 2009), respectively. A rich body of respirometry-based literature has laid the groundwork for the basic understanding of tuna life-history traits (e.g., Dewar and Graham, 1994; Korsmeyer et al., 1996), but relatively few studies have taken a comprehensive, full life cycle perspective (sensu Jusup et al., 2011; Jusup et al., 2014) to explain the differences between species in terms of physiological constraints. Herein we seek to fill this latter gap in particular.
Comparative physiology has relied on a multitude of methodologies to study the diversity of functional characteristics of organisms (Garland Jr. and Carter, 1994). While there is no single preferred methodology, we used the principles of physiological energetics (Jusup and Matsuda, 2015) as a basis for comparing three commercial tuna species: Atlantic bluefin, Pacific bluefin, and skipjack. More specifically, we based our study on the general framework of Dynamic Energy Budget (DEB) theory for building individual-based energetics models (Nisbet et al., 2000; Kooijman, 2010; Jusup et al., 2017). DEB theory derives metabolic processes of an organism as a function of food intake and temperature from the first principles (e.g., mass-energy conservation laws, homeostasis of organisms, etc.). The theory, furthermore, specifies interspecies scaling relationships (Kooijman, 2010; Jusup et al., 2017) needed to explain the well-known patterns in the measured field data (e.g., Schmidt-Nielsen, 1972). Here, we seek to identify the mechanistic origins of the large differences in, e.g., body size between tunas, but also to understand the mechanisms from which common tuna life-history traits arise.
We built on an existing (Jusup et al., 2011), calibrated and validated (Jusup et al., 2014), full life cycle model for PBT—from an egg to an adult individual and its eggs. We updated the parameters of this model to capture additional minute details of the PBT life-history (e.g., egg dry mass), and then used the resulting parameter values in conjunction with the covariation method (Lika et al., 2011) to adapt the same model to SKJ and ABT. We then reconstructed the energy budgets of all three species and described the probable mechanisms behind various tuna life-history traits. Finally, we discussed these results in terms of tuna physiology, ecology, and evolution.
Section snippets
Model outline
Because a comprehensive description of the DEB model for tuna can be found elsewhere in the literature (Jusup et al., 2011, Jusup et al., 2014), here we focus on key concepts and give further mathematical details in the Supporting Information (SI) Methods. Conceptually, all DEB models can be characterised by the equationwhere L is fish size, a is age, and Ġ = Ġ(i-state, e-state) is a growth function that depends on the state of this fish (i-state), as well as the
Goodness of fit
The tuna DEB model produces satisfactory fits to exhaustive datasets (Table S1) that encompass the whole lifecycle of all three tuna species (Fig. 1, Fig. 2; Table 1). Using a goodness-of-fit (GOF) scale from 0 for a complete mismatch to 100 for a perfect fit (SI Methods), we find that GOFSKJ = 90.1, GOFPBT = 95.0, and GOFABT = 93.0, thus quantitatively confirming that the model's precision is favourable for all three studied species.
In the embryonic stage, hatching as a function of temperature
Discussion
We developed novel Dynamic Energy Budget (DEB) models for skipjack (SKJ) and Atlantic bluefin (ABT) tunas, as well as updated a previously published model for Pacific bluefin tuna (PBT; Jusup et al., 2011, Jusup et al., 2014). These models successfully fit the data from all life stages of the three studied species—from an egg to an adult individual and its eggs—revealing in the process the underlying physiological energetics in terms of environment-dependent energy budgets. Here, we primarily
Conclusion
At the heart of the present study is the causation between the characteristics of larval and early juvenile tuna and the characteristics of adult tuna. This causation is threefold:
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Tuna larvae undergo morphological and physiological transformations that increase energy assimilation (input into reserve) and utilisation (output from reserve). The increase is dramatic. By the end of the larval stage, for example, SKJ, PBT, and ABT assimilate energy at rates M1{ṗAm} = 2273 J·cm−2·d−1, 3137 J·cm−2·d−1
Acknowledgments
We thank H. Ijima, H. Matsuda, and T. Klanjšček for useful discussions. M.J. was supported by the Research Grant Program of Inamori Foundation. T.K. was partially supported by CREST funding program from Japan Science and Technology Agency (JST), grant-in-aid for Scientific Research (A) (No. 16H01769), and grant-in-aid for Scientific Research (B) (No. 24380104) from the Japan Society for the Promotion of Science (JSPS).
Author's contributions
Y.A., M.J., and A-E.N. conceived the research; Y.A. and M.J. conducted simulations; all authors interpreted the results and wrote the manuscript. Y.A. and M.J. contributed equally.
Data accessibility
All data is available upon request from the corresponding author.
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