As is commonly done for many animals where direct observation of foraging is difficult, foraging areas of pygmy blue whales have previously been defined from analysis of data obtained from satellite tracking tags deployed on pygmy blue whales. These studies (Double et al. 2014, Moller et al. 2020 and Thums et al. 2022) documented pygmy blue whale migration between Australia and Indonesia and identified areas where whales spent the most time and where they had movement behaviour (as calculated from surface location estimates from the tags) thought to be indicative of foraging (slower speed and lots of turns), such as the Bonny upwelling region of South Australia, Perth Canyon, NW Cape region and the Banda Sea. Although there is a theoretical basis for assigning putative foraging behaviour along the horizontal movement paths of animals based on such analyses of location estimates from satellite tags (Kareiva & Odell 1987, Zollner & Lima 1999), foraging actually occurs while the animals are diving and so having data from the vertical dimension is important for validation of foraging areas defined using these methods.
To characterise and track vertical movement behaviours and validate inferred foraging behaviour from movement models, eight pygmy blue whales were double tagged by AIMS and CWR (in partnership with Woodside) in the Perth Canyon, Western Australia with Fastloc GPS tags (Wildlife Computers LIMPET; Low Impact Minimally Percutaneous Electronic Transmitters, type: SPLASH10-F-333) and pop-up satellite-linked archival tags (PSATs) (Wildlife Computers MiniPAT) in 2021 – 2022, and another double tagged at Ningaloo in 2023. The GPS tags provided location estimates and the PSATs provided depth and summarised accelerometery time-series (Mobility and activity-time series, ATS) data from the whales for up to 40 d duration, encompassing presumed foraging grounds and migration areas. Four PSATs were recovered, providing access to the high-resolution (1 s sample rate of depth and Mobility) data archive on board the tag. For the remaining five tags, the summarised time-series data (75 s sample rate of depth and ATS) transmitted through the Argos satellite network (Argos), was used for the analysis. Given the difficulty of recovering tags from long (> a few days) deployments, both recovered and transmitted datasets were used to determine whether lower temporal resolution depth and accelerometry data transmitted via Argos (compared to the archived data on board recovered tags) can provide sufficient detail to characterise pygmy blue whale diving behaviour, especially foraging and feeding. Diving behaviour was characterised using a supervised Random Forests dive behaviour classification function to determine where and when pygmy blue whales forage. The locations where foraging and lunge feeding dives occurred was compared to areas of putative foraging inferred from a movement model (State-space model) and to important foraging areas previously defined from spatial analyses based on horizontal movement data only (Thums et al. 2022).
Transmitted depth time series (75s) was adequate for identifying foraging dives, but accelerometry metrics were key (error increased to 18% without it) to distinguishing lunge feeding dives from foraging dives without lunges.
Foraging and lunge feeding dives occurred in three main foraging areas: 1) Centred at the head of the Perth Canyon, extending from offshore of Cape Naturaliste to offshore of Jurien Bay, 2) offshore of Geraldton and the Abrolhos Islands and 3) offshore of Ningaloo, extending from approximately Coral Bay up to offshore of approximately the Montebello Islands (~19 °S). Foraging/ feeding was also detected in the Savu Sea (~8 °S), offshore of Bremer Bay and far off the shelf of the Kimberley region of Western Australia while migrating (~15 °S, ~120 °E).
Despite a weak temporal relationship between putative (inferred from a movement model) and actual foraging, there was generally good spatial overlap detected, but predominantly in high use areas with lower use and more opportunistic foraging areas being less likely to be detected by the model. More opportunistic foraging occurred off north-west Australia where foraging dives were shallower, horizontal travel rates faster, and there was an absence of a diurnal pattern in diving. This suggests a reliance on more ephemeral prey than off south-west Australia where whales have high residency.
Our test of movement models to define foraging areas is extremely useful given its common usage in ecology and our spatial delineation of foraging areas assists with conservation management.
