How animals distribute themselves in space: variable energy landscapes

• Published in: Frontiers in Zoology
• Main Authors: Juan F. Masello, Akiko Kato, Julia Sommerfeld, Thomas Mattern, Petra Quillfeldt
• Format: Article in Journal/Newspaper
• Language: English
• Published: BMC 2017
• Subjects: Energetic costs; Energy landscape; Foraging effort; Foraging strategy; Landscape of fear; Ecological mechanism; Zoology; QL1-991; Pygoscelis papua
• Online Access: https://doi.org/10.1186/s12983-017-0219-8; https://doaj.org/article/cd70e5a439a9428d816d09f72aae7485

Abstract Background Foraging efficiency determines whether animals will be able to raise healthy broods, maintain their own condition, avoid predators and ultimately increase their fitness. Using accelerometers and GPS loggers, features of the habitat and the way animals deal with variable conditions can be translated into energetic costs of movement, which, in turn, can be translated to energy landscapes.We investigated energy landscapes in Gentoo Penguins Pygoscelis papua from two colonies at New Island, Falkland/Malvinas Islands. Results In our study, the marine areas used by the penguins, parameters of dive depth and the proportion of pelagic and benthic dives varied both between years and colonies. As a consequence, the energy landscapes also varied between the years, and we discuss how this was related to differences in food availability, which were also reflected in differences in carbon and nitrogen stable isotope values and isotopic niche metrics. In the second year, the energy landscape was characterized by lower foraging costs per energy gain, and breeding success was also higher in this year. Additionally, an area around three South American Fur Seal Arctocephalus australis colonies was never used. Conclusions These results confirm that energy landscapes vary in time and that the seabirds forage in areas of the energy landscapes that result in minimized energetic costs. Thus, our results support the view of energy landscapes and fear of predation as mechanisms underlying animal foraging behaviour. Furthermore, we show that energy landscapes are useful in linking energy gain and variable energy costs of foraging to breeding success.