Variability in prey field structure drives inter-annual differences in prey encounter by a marine predator, the little penguin

Abstract

Understanding how marine predators encounter prey across patchy landscapes remains challenging due to difficulties in measuring the three-dimensional structure of pelagic prey fields at scales relevant to animal movement. We measured at-sea behaviour of a central-place forager, the little penguin ( Eudyptula minor ), over 5 years (2015–2019) using GPS and dive loggers. We made contemporaneous measurements of the prey field within the penguins' foraging range via boat-based acoustic surveys. We developed a prey encounter index by comparing estimates of acoustic prey density encountered along actual penguin tracks to those encountered along simulated penguin tracks with the same characteristics as real tracks but that moved randomly through the prey field. In most years, penguin tracks encountered prey better than simulated random movements greater than 99% of the time, and penguin dive depths matched peaks in the vertical distribution of prey. However, when prey was unusually sparse and/or deep, penguins had worse than random prey encounter indices, exhibited dives that mismatched depth of maximum prey density, and females had abnormally low body mass (5.3% lower than average). Reductions in prey encounters owing to decreases in the density or accessibility of prey may ultimately lead to reduced fitness and population declines in central-place foraging marine predators.

aniMotum, an R package for animal movement data: Rapid quality control, behavioural estimation and simulation

“…To illustrate how move persistence () can be estimated from GPS data, we use four little penguin Eudyptula minor tracks of daily foraging trips during the chick‐rearing period from Montague Island, NSW, Australia (described in Phillips et al, 2022). The data are temporally irregular GPS locations, with high‐frequency sampling (mean 15 s) intermittently disrupted by the birds' diving behaviour, and are assumed to have minimal measurement error.…”

Links between the three-dimensional movements of whale sharks (Rhincodon typus) and the bio-physical environment off a coral reef

“…Acoustic surveys enable the quantification of pelagic prey-field metrics (e.g., prey field depth and density) at spatial and temporal resolutions comparable to the movement patterns and behaviour of marine predators [ 17 , 18 ]. Such methods have enabled a number of studies to describe the movement patterns of air-breathing marine predators (e.g., pinnipeds, rorqual whales and penguins) in relation to surrounding prey fields across meso- scales (10–100 s km; [ 19 , 20 ]), sub-mesoscale (1–10 km; [ 15 ]) or local (meters) spatial scales [ 21 ]. For example, rorqual whales have been shown to alter their diving behaviour [ 22 ] and concentrate foraging efforts [ 15 , 23 ] in relation to prey densities and distribution.…”