No abstract

It is obvious, at least qualitatively, that small animals move their locomotory apparatus faster than large animals: small insects move their wings invisibly fast, while large birds flap their wings slowly. However, quantitative observations have been difficult to obtain from free-ranging swimming animals. We surveyed the swimming behaviour of animals ranging from 0.5 kg seabirds to 30 000 kg sperm whales using animalborne accelerometers. Dominant stroke cycle frequencies of swimming specialist seabirds and marine mammals were proportional to mass K0.29 (R 2 Z0.99, nZ17 groups), while propulsive swimming speeds of 1-2 m s K1 were independent of body size. This scaling relationship, obtained from breath-hold divers expected to swim optimally to conserve oxygen, does not agree with recent theoretical predictions for optimal swimming. Seabirds that use their wings for both swimming and flying stroked at a lower frequency than other swimming specialists of the same size, suggesting a morphological trade-off with wing size and stroke frequency representing a compromise. In contrast, foot-propelled diving birds such as shags had similar stroke frequencies as other swimming specialists. These results suggest that muscle characteristics may constrain swimming during cruising travel, with convergence among diving specialists in the proportions and contraction rates of propulsive muscles.

In a patchy environment, predators are expected to increase turning rate and start an area-restricted search (ARS) when prey have been encountered, but few empirical data exist for large predators. By using GPS loggers with devices measuring prey capture, we studied how a marine predator adjusts foraging movements at various scales in relation to prey capture. Wandering albatrosses use two tactics, sit and wait and foraging in flight, the former tactic being three times less efficient than the latter. During flight foraging, birds caught large isolated prey and used ARS at scales varying from 5 to 90 km, with large-scale ARS being used only by young animals. Birds did not show strong responses to prey capture at a large scale, few ARS events occurred after prey capture, and birds did not have high rates of prey capture in ARS. Only at small scales did birds increase sinuosity after prey captures for a limited time period, and this occurred only after they had caught a large prey item within an ARS zone. When this species searches over a large scale, the most effective search rule was to follow a nearly straight path. ARS may be used to restrict search to a particular environment where prey capture is more predictable and profitable.

These datasets and accompanying syntheses provide a greater understanding of fundamental ecosystem processes in the Southern Ocean, support modelling of predator distributions under future climate scenarios and create inputs that can be incorporated into decision making processes by management authorities. In this data paper, we present the compiled tracking data from research groups that have worked in the Antarctic since the 1990s. The data are publicly available through biodiversity.aq and the Ocean Biogeographic Information System. The archive includes tracking data from over 70 contributors across 12 national Antarctic programs, and includes data from 17 predator species, 4060 individual animals, and over 2.9 million observed locations.Scientific Data | (2020) 7:94 | https://doi.org/10.1038/s41597-020-0406-x www.nature.com/scientificdata www.nature.com/scientificdata/ circum-Antarctic synthesis yet exists that crosses species boundaries. This deficiency prompted the Expert Group on Birds and Marine Mammals (EG-BAMM) and the Expert Group on Antarctic Biodiversity Informatics (EGABI) of the Scientific Committee on Antarctic Research (SCAR; www.scar.org) to initiate in 2010 the Retrospective Analysis of Antarctic Tracking Data (RAATD). RAATD aims to advance our understanding of fundamental and applied questions in a data-driven way, matching research priorities already identified by the SCAR Horizon Scan 9,21 and key questions in animal movement ecology 22 . For these reasons, we worked on the collation, validation and preparation of tracking data collected south of 45 °S. Data from over seventy contributors (Data Contacts and Citations 23 ) were collated. This database includes information from seventeen predator species, 4,060 individuals and over 2.9 million at-sea locations. To exploit this unique dataset, RAATD is undertaking a multi-species assessment of habitat use for higher predators in the Southern Ocean 24 .RAATD will provide a greater understanding of predator distributions under varying climate regimes, and provide outputs that can inform spatial management and planning decisions by management authorities such as the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR; www.ccamlr.org). Our synopsis and analysis of multi-predator tracking data will also highlight regional or seasonal data-gaps.Scientific Data | (2020) 7:94 | https://doi.