Abstract
BackgroundEnergy landscapes provide an approach to the mechanistic basis of spatial ecology and decision-making in animals. This is based on the quantification of the variation in the energy costs of movements through a given environment, as well as how these costs vary in time and for different animal populations. Organisms as diverse as fish, mammals, and birds will move in areas of the energy landscape that result in minimised costs and maximised energy gain. Recently, energy landscapes have been used to link energy gain and variable energy costs of foraging to breeding success, revealing their potential use for understanding demographic changes.MethodsUsing GPS-temperature-depth and tri-axial accelerometer loggers, stable isotope and molecular analyses of the diet, and leucocyte counts, we studied the response of gentoo (Pygoscelis papua) and chinstrap (Pygoscelis antarcticus) penguins to different energy landscapes and resources. We compared species and gentoo penguin populations with contrasting population trends.ResultsBetween populations, gentoo penguins from Livingston Island (Antarctica), a site with positive population trends, foraged in energy landscape sectors that implied lower foraging costs per energy gained compared with those around New Island (Falkland/Malvinas Islands; sub-Antarctic), a breeding site with fluctuating energy costs of foraging, breeding success and populations. Between species, chinstrap penguins foraged in sectors of the energy landscape with lower foraging costs per bottom time, a proxy for energy gain. They also showed lower physiological stress, as revealed by leucocyte counts, and higher breeding success than gentoo penguins. In terms of diet, we found a flexible foraging ecology in gentoo penguins but a narrow foraging niche for chinstraps.ConclusionsThe lower foraging costs incurred by the gentoo penguins from Livingston, may favour a higher breeding success that would explain the species’ positive population trend in the Antarctic Peninsula. The lower foraging costs in chinstrap penguins may also explain their higher breeding success, compared to gentoos from Antarctica but not their negative population trend. Altogether, our results suggest a link between energy landscapes and breeding success mediated by the physiological condition.
Highlights
Energy landscapes provide an approach to the mechanistic basis of spatial ecology and decisionmaking in animals
We found that the sum of Overall Dynamic Body Acceleration (ODBA) during the dives carried out by the penguins was related to the maximum dive depth they reached
Foraging trips and dive parameters In Antarctica, both gentoos and chinstraps foraged relatively close to their own colonies (Fig. 2), using the colony’s ‘hinterland’ and avoided areas closer to the neighbouring colonies and those from potential predators (Additional file 1, Fig. S18), and performed trips with the usual loop shape (Fig. 2)
Summary
Energy landscapes provide an approach to the mechanistic basis of spatial ecology and decisionmaking in animals This is based on the quantification of the variation in the energy costs of movements through a given environment, as well as how these costs vary in time and for different animal populations. The first systematic attempts to understand the role of behaviour in the distribution of animals originated from optimal foraging theory [13, 14] In this context, animals should exhibit behaviours that maximize energetic efficiency, selecting patches where the gain per unit cost is high, and the energy expenditure to reach them is minimized. Research conducted in organisms as diverse as fish, mammals, and birds showed that animals will move in areas of the energy landscape that result in minimized costs and maximised energy gain [19, 21, 23, 25,26,27]
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