DOI: 10.5061/dryad.vdncjsxzb
title: Data for: Hunting behavior of a solitary sailfish Istiophorus platypterus and estimated energy gain after prey capture

description: Foraging behavior and interaction with prey is an integral component of
 the niche of predators but is inherently difficult to observe for highly
 mobile animals in the marine environment. Billfish have been described as
 ‘energy speculators’, expending a large amount of energy foraging,
 expecting to offset high costs with periodic high energetic gain.
 Surface-based group feeding of sailfish, Istiophorus platypterus, is
 commonly observed, yet sailfish are believed to be solitary roaming
 predators with high metabolic requirements, suggesting that individual
 foraging also represents a major component of predator-prey interactions.
 Here, we use biologging data and video to examine daily activity levels
 and foraging behavior, estimate metabolic costs, and document a solitary
 predation event. We estimate a median active metabolic rate of 218.9 ±
 70.5 mgO2 kg-1 h-1 which increased to 518.8 ± 586.3 mgO2 kg-1 h-1 during
 prey pursuit. Assuming a successful predation, we estimate a daily net
 energy gain of 2.4 MJ (5.1 MJ acquired, 2.7 MJ expended), supporting the
 energy speculator model. While group hunting may be a common activity used
 by sailfish to acquire energy, our calculations indicate that
 opportunistic individual foraging events offer a net energy return that
 contributes to the fitness of these highly mobile predators. 
description: Data were analyzed using Igor Pro v. 8.0.4.2 (Wavemetrics, Inc.,
 Lake Oswego, OR, USA) and RStudio v. 1.4.1106 [19]. The static component
 of acceleration was calculated using a 3-s box smoothing window on the raw
 acceleration data [20]. Tag attachment angle was corrected by rotating the
 raw acceleration data such that the X and Y axis had a mean of zero. Body
 pitch was then calculated from the anterior-posterior axis of the static
 component of acceleration. The lateral axis of the gyroscope was used to
 determine directionality of the strikes during the predation event, and
 calculate the tailbeat frequency using a continuous wavelet transformation
 [21, 22]. Finally, a compass heading and pseudo track were generated from
 the magnetometer data using the <em>magHead</em> function in
 the gRumble R package [23]. To estimate the sailfish’s
 active metabolic rate and energy expenditure, we used the relationship
 between oxygen consumption and swim speed for adult dolphinfish
 (<em>Coryphaena hippurus</em>) [24], with the assumption this
 relationship is consistent across fish length [25, 26]. See section 2 of
 the supplementary material for a detailed description of why dolphinfish
 was chosen as the proxy species and further description of metabolic rate
 calculations. Oxygen consumption
 (<em>M</em>O<sub>2</sub>;
 mgO<sub>2</sub> kg<sup>-1</sup>
 h<sup>-1</sup>) was estimated using the equation
 log(<em>M</em>O<sub>2</sub>) =
 [c<em>U</em> + log(d)], where c and d are the slope and
 intercept of the logarithmic regression, and <em>U</em> is the
 swim speed of the sailfish (BLs<sup>-1</sup>; Figure S3).
 <em>M</em>O<sub>2</sub> was calculated
 continuously for every speed measurement throughout the 24 hours from the
 sailfish tag data, and we then took the inverse log of
 <em>M</em>O<sub>2</sub> and corrected for mass of
 the dolphinfish (M<sub>D</sub>) in [24] to obtain
 <em>V</em>O<sub>2</sub> (mgO<sub>2
 </sub>h<sup>-1</sup>). Oxygen consumption for the 40 kg
 sailfish was then calculated using the equation:  AMR<sub>E</sub> =
 <em>V</em>O<sub>2</sub> *
 (M<sub>S</sub>/M<sub>d</sub>)<sup>b</sup> where AMR<sub>E</sub> is the estimated active metabolic rate (mgO<sub>2</sub> h<sup>-1</sup>), <em>V</em>O<sub>2</sub> is the oxygen consumption at each swim speed, b is the mass scaling exponent, and M<sub>S</sub> is the sailfish mass (kg). AMR<sub>E</sub> was corrected for temperature using a Q<sub>10</sub> of 1.83 [27, 28] and was made mass-specific using the estimated mass of the sailfish.<sup> </sup> References 19. Holland, K. N. et al. Physiological and behavioural thermoregulation in bigeye tuna (<em>Thunnus</em> <em>obesus</em>). Nature 358(6385), 410–412 (1992). 20. Nakamura, I., Goto, Y. & Sato, K. Ocean sunfish rewarm at the surface after deep excursions to forage for siphonophores. J. Anim. Ecol. 84(3), 590–603 (2015). 21. Watanabe, Y. Y., Nakamura, I. & Chiang, W.-C. Behavioural thermoregulation linked to foraging in blue sharks. Mar. Biol. 168(11), 1–10 (2021). 22. Sepulveda, C. A. et al. Movements and behaviors of swordfish <em>Xiphias</em> <em>gladius</em> in the United States pacific leatherback conservation area. Fish. Oceanogr. 27(4), 381–394 (2018). 23. Rohner, C. A. et al. Vertical habitat use by black and striped marlin in the Western Indian Ocean. Mar. Ecol. Prog. Ser. 690, 165–183 (2022). 24. Block, B. A., Booth, D. & Carey, F. G. Direct measurement of swimming speeds and depth of blue marlin. J. Exp. Biol. 166(1), 267–284 (1992). 25. Collette, B.B. & C. Aadland, Revision of the frigate tunas (Scombridae, <em>Auxis</em>), with descriptions of two new subspecies from the eastern Pacific. Fish. Bull. (1996). 26. Abitia-Cardenas, L. A., Galvan-Magaña, F. & Rodriguez-Romero, J. Food habits and energy values of prey of striped marlin, <em>Tetrapturus</em> <em>audax</em>, off the coast of Mexico. Fish. Bull. 95, 360–368 (1997). 27. Lane, F. How fast do fish swim. Country Life (London) 90, 534–535 (1941). 28. Svendsen, M. B. et al. Maximum swimming speeds of sailfish and three other large marine predatory fish species based on muscle contraction time and stride length: a myth revisited. Biol. Open 5(10), 1415–1419 (2016).