How animals distribute themselves in space: energy landscapes of Antarctic avian predators

Abstract

Background Energy 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. Methods Using 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. Results Between 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. Conclusions The 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.

Mercury Levels in Feathers of Penguins from the Antarctic Peninsula Area: Geographical and Inter-Specific Differences

“…Regarding interspecific differences, we found that chinstrap penguin samples contained the highest Hg levels in two locations (Livingston I. and Ronge I., Figure 4 ), while we did not find interspecific differences in King George I. These results do not support our prediction that a higher trophic niche could be related to higher mercury level due to bioaccumulation and biomagnification processes, as the gentoo penguin usually has a diet including more fishes and cephalopods, therefore occupying a higher trophic niche, than the chinstrap penguin, which shows a diet with a higher percentage of krill [ 23 , 24 , 27 ]. This coincides with what was described by Brasso et al [ 26 ], which affirms that inter- and intra-specific differences in eggshell membrane mercury concentrations of the same three species of penguins were not related to eggshell δ15N or δ13C values.…”

“…Differences in habitat use pelagic/offshore in the chinstrap and benthic/inshore in the gentoo and the higher krill consumption of chinstrap [ 27 ] could explain the differences found. Another explanation could involve physiological differences among species such as different capacities for detoxification and elimination of Hg or different absorption-elimination rates.…”

Energy landscapes of Kodiak brown bears: A comparison of accelerometer and global positioning system derived estimates

“…To create a visual example of energetic measurements from the GPS and ACC methods, we used the inverse distance weighted interpolation tool in ArcGIS (Childs, 2004) to construct four energy landscapes for an individual male and female brown bear on Afognak island. We used the inverse distance weighted interpolation tool as we had a large sample of location data that represented the range of observed values for that energy surface (Masello et al 2021).…”

Using Next-Generation Sequencing to Disentangle the Diet and Incidence of Intestinal Parasites of Falkland Flightless Steamer Duck Tachyeres brachypterus and Patagonian Crested Duck Lophonetta specularioides Sharing a South Atlantic Island

“…Analyses of the food consumed by animal species sharing a habitat can facilitate our understanding of the mechanistic processes in a community and the different functions of the organisms in an ecosystem [ 10 ]. Dietary studies give vital insights into foraging behavior [ 11 ] and prey species occurrence and abundance [ 12 ], with implications for understanding environmental change and its impact on wildlife [ 13 , 14 , 15 ]. However, detailed knowledge on the diet of a species can be difficult to obtain, particularly for small, nocturnal, beneath-the-soil, underwater, oceanic or elusive species [ 10 , 16 ].…”

“…Moreover, the development of next-generation sequencing (NGS) has allowed for the identification of prey items of several samples up to the species level in a single sequencing run while upholding the ability to trace each prey back to the sample of origin [ 23 , 24 ]. As a consequence, NGS is increasingly being used for diet studies [ 11 , 25 , 26 ], with feces being the least invasive and most widespread sample type [ 21 , 27 , 28 ].…”