Abstract
Foraging in the marine environment presents particular challenges for air-breathing predators. Information about prey capture rates, the strategies that diving predators use to maximise prey encounter rates and foraging success are still largely unknown and difficult to observe. As well, with the growing awareness of potential climate change impacts and the increasing interest in the development of renewable sources it is unknown how the foraging activity of diving predators such as seabirds will respond to both the presence of underwater structures and the potential corresponding changes in prey distributions. Motivated by this issue we developed a theoretical model to gain general understanding of how the foraging efficiency of diving predators may vary according to landscape structure and foraging strategy. Our theoretical model highlights that animal movements, intervals between prey capture and foraging efficiency are likely to critically depend on the distribution of the prey resource and the size and distribution of introduced underwater structures. For multiple prey loaders, changes in prey distribution affected the searching time necessary to catch a set amount of prey which in turn affected the foraging efficiency. The spatial aggregation of prey around small devices (∼ 9 × 9 m) created a valuable habitat for a successful foraging activity resulting in shorter intervals between prey captures and higher foraging efficiency. The presence of large devices (∼ 24 × 24 m) however represented an obstacle for predator movement, thus increasing the intervals between prey captures. In contrast, for single prey loaders the introduction of spatial aggregation of the resources did not represent an advantage suggesting that their foraging efficiency is more strongly affected by other factors such as the timing to find the first prey item which was found to occur faster in the presence of large devices. The development of this theoretical model represents a useful starting point to understand the energetic reasons for a range of potential predator responses to spatial heterogeneity and environmental uncertainties in terms of search behaviour and predator–prey interactions. We highlight future directions that integrated empirical and modelling studies should take to improve our ability to predict how diving predators will be impacted by the deployment of manmade structures in the marine environment.
Highlights
Foraging theory is well-developed and has importance for applied ecological problems with examples including the management of large herbivores (Belovsky, 1991), the effectiveness of biological agents in controlling pest populations (Railsback & Johnson, 2011), and most recently in the development of strategies for mitigating human-wildlife conflicts (Baruch-Mordo et al, 2012)
Our aim is to gain theoretical understanding of the foraging efficiency of diving predators characterised by different foraging strategies in complex marine landscapes
We focused on the vertical movements in order to understand at a finer scale the dynamics of a diving predator encountering its prey and the effects of different prey distributions and habitat heterogeneity characteristics
Summary
Foraging theory is well-developed and has importance for applied ecological problems with examples including the management of large herbivores (Belovsky, 1991), the effectiveness of biological agents in controlling pest populations (Railsback & Johnson, 2011), and most recently in the development of strategies for mitigating human-wildlife conflicts (Baruch-Mordo et al, 2012). There is currently substantial interest in the foraging behaviour of diving marine predators especially in the context of how this may be influenced by the deployment of marine renewable devices. In this contribution we develop a strategic model to represent, in a highly abstracted way, the foraging behaviour of diving seabirds in environments that can include changes to habitat heterogeneity. Later models accounted for imperfect information and assumed random and unpredictable resource environments (Bovet & Benhamou, 1991; Bartumeus et al, 2005; Conradt et al, 2003). The information received determined how long a forager will stay in a particular patch (Green, 1980; Olsson & Holmgren, 1998; Valone, 1992)
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