Carl G. Meyer

Cruising speed is a key factor affecting prey-search efficiency and migration range in continuously swimming animals. Tunas and lamnid sharks (e.g., white sharks) have convergently evolved traits for high-speed cruising, including the ability to maintain slow-twitch, aerobic red muscle (RM) warmer than ambient water, known as RM endothermy. Despite their well-known high cruising speeds, kinematic features underlying their elevated speeds remain unclear. Swim speed is the product of tailbeat frequency (TBF; Hz) and stride length (SL, the absolute distance traveled per tailbeat; m). RM endothermy is expected to elevate TBF by enhancing muscle contraction performance. Furthermore, within RM-endothermic fishes, tunas and lamnid sharks may exhibit distinct kinematic features because of differences in caudal fin morphology and tailbeat amplitude. Here, we compiled kinematic parameters from 20 fish species, including five RM-endothermic species, measured in the wild using animal-borne sensors. Comparative analyses showed that, for a given body mass and water temperature, RM-endothermic fishes exhibited 1.9 times higher cruising speed and TBF than ectothermic fishes, while SL remained similar. Within RM-endothermic fishes, tunas exhibited 2.3 times higher TBF than similar-sized lamnid sharks, whereas lamnid sharks showed 1.7 times longer SL than similar-sized tunas. These results indicate that RM endothermy is generally associated with higher TBF, while significant kinematic differences remain between tunas and lamnid sharks. This divergence may be partly explained by the greater caudal fin area and tailbeat amplitude in lamnid sharks. It may also reflect contrasting skeletal types of teleosts and elasmobranchs, which potentially influence body stiffness and swimming kinematics.

Oceanic whitetip sharks (Carcharhinus longimanus) are critically endangered and frequently interact with pelagic longline fisheries, yet the drivers of bycatch risk and the interpretation of catch-per-unit-effort (CPUE) trends remain poorly resolved. Using U.S. National Marine Fisheries Service observer data from the Hawaiʻi-based pelagic longline fleet (1994–2025; ~118,000 sets; ~250 million hooks), I quantified spatiotemporal structure, environmental drivers, long-term trends, and gear-related effects in oceanic whitetip shark (OWT) bycatch. Sector-stratified delta generalized additive models were used to separately model encounter probability and positive catch magnitude as functions of spatial location, bathymetric proximity, seasonal effects, dynamic oceanographic conditions, and climate variability. OWT encounter probability was strongly spatially aggregated into persistent hotspots. Deep-set hotspots occurred primarily at lower tropical latitudes in offshore pelagic habitat, whereas shallow-set hotspots were more closely associated with shelf-edge proximity. Encounter probability was significantly structured by surface oceanography (SST, chlorophyll-a, SSH) and ENSO variability, while conditional catch magnitude showed weaker environmental dependence. Although nominal CPUE declined significantly in both sectors (Kendall’s τ = −0.37 deep; −0.58 shallow), a space-standardized index constructed under a fixed reference fishing footprint showed an early decline followed by relatively stable encounter rates, indicating that part of the nominal decline reflects redistribution of fishing effort relative to spatially structured encounter risk. Following the 2020–2022 transition from wire to monofilament leaders, positive catch magnitude declined while encounter probability remained unchanged, consistent with reduced retention rather than altered encounter processes. A simple spatial mitigation scenario indicated that avoiding fishing effort south of 10°N, representing ~2% of deep-set effort, would target ~23% of the space-standardized predicted encounter risk while imposing ~1% loss in target catch. These results highlight the importance of separating ecological change from fleet redistribution when interpreting bycatch trends and identify opportunities for spatially informed mitigation in pelagic longline fisheries.