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. 

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 magHead 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 (Coryphaena hippurus) [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 (MO₂; mgO₂ kg^-1 h^-1) was estimated using the equation log(MO₂) = [cU + log(d)], where c and d are the slope and intercept of the logarithmic regression, and U is the swim speed of the sailfish (BLs^-1; Figure S3). MO₂ was calculated continuously for every speed measurement throughout the 24 hours from the sailfish tag data, and we then took the inverse log of MO₂ and corrected for mass of the dolphinfish (M_D) in [24] to obtain VO₂ (mgO₂ h^-1). Oxygen consumption for the 40 kg sailfish was then calculated using the equation:

 AMR_E = VO₂ * (M_S/M_d)^b

where AMR_E is the estimated active metabolic rate (mgO₂ h^-1), VO₂ is the oxygen consumption at each swim speed, b is the mass scaling exponent, and M_S is the sailfish mass (kg). AMR_E was corrected for temperature using a Q₁₀ of 1.83 [27, 28] and was made mass-specific using the estimated mass of the sailfish. 

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