Abstract: Solar geolocation is used to quantify the movements of animals tagged with sensors that record ambient light with respect to time. Global location sensor (GLS) tags are small, light, and present minimal drag or wing loading. They are affordable, and some can record data for several migratory cycles. These benefits mean they can be used in applications for which satellite tags are unsuitable. However, large errors in estimated locations can result if the sensor is obscured, especially around twilight, and sometimes the data obtained is unusable by existing methods of analysis due to this source of noise. This places limitations on the usefulness of solar geolocation in conservation and monitoring efforts. All existing methods of analysis are dependent on twilights being identifiable or faithfully recorded. Instead, the method introduced here depends on the overall pattern of day and night to calculate the likelihoods for a Hidden Markov Model, where the hidden states are geographic locations. We call this a “twilight-free” method of light-based geolocation. This method quickly estimates locations from otherwise unusable noisy light data. We use examples to show that the method produces tracks that are comparable in accuracy and precision to other geolocation methods. Furthermore, efficiency and replicability of estimated paths are improved because the user does not have to subjectively identify twilights. Other data sources, such as sea surface temperature and land or sea masks are easily incorporated, further improving location estimates and processing speed. The twilight-free method offers new opportunities to researchers interested in the movements of animals that routinely have obscured sensors, or to analyse previously unusable noisy light data. It offers a fast, efficient, and replicable method for analysing tag data without the need for time-consuming pre- or post-processing. By increasing the yield of usable data from GLS tagging studies, researchers can more efficiently quantify where animals are going and when, and monitor changes in habitat. This is of fundamental importance to management and conservation efforts.

Abstract: Despite playing a major role in global ocean heat storage, the Southern Ocean remains the most sparsely measured region of the global ocean. Here, a unique 25-year temperature time-series of the upper 800 m, repeated several times a year across the Southern Ocean, allows us to document the long-term change within water-masses and how it compares to the interannual variability. Three regions stand out as having strong trends that dominate over interannual variability: warming of the subantarctic waters (0.29 ± 0.09 °C per decade); cooling of the near-surface subpolar waters (−0.07 ± 0.04 °C per decade); and warming of the subsurface subpolar deep waters (0.04 ± 0.01 °C per decade). Although this subsurface warming of subpolar deep waters is small, it is the most robust long-term trend of our section, being in a region with weak interannual variability. This robust warming is associated with a large shoaling of the maximum temperature core in the subpolar deep water (39 ± 09 m per decade), which has been significantly underestimated by a factor of 3 to 10 in past studies. We find temperature changes of comparable magnitude to those reported in Amundsen–Bellingshausen Seas, which calls for a reconsideration of current ocean changes with important consequences for our understanding of future Antarctic ice-sheet mass loss.

Abstract: Defining reliable demographic models is essential to understand the threats of ongoing environmental change. Yet, in the most remote and threatened areas, models are often based on the survey of a single population, assuming stationarity and independence in population responses. This is the case for the Emperor penguin Aptenodytes forsteri, a flagship Antarctic species that may be at high risk continent-wide before 2100. Here, using genome-wide data from the whole Antarctic continent, we reveal that this top-predator is organized as one single global population with a shared demography since the late Quaternary. We refute the view of the local population as a relevant demographic unit, and highlight that (i) robust extinction risk estimations are only possible by including dispersal rates and (ii) colony-scaled population size is rather indicative of local stochastic events, whereas the species’ response to global environmental change is likely to follow a shared evolutionary trajectory.

Abstract: Penguins lost the ability to fly more than 60 million years ago, subsequently evolving a hyper-specialized marine body plan. Within the framework of a genome-scale, fossil-inclusive phylogeny, we identify key geological events that shaped penguin diversification and genomic signatures consistent with widespread refugia/recolonization during major climate oscillations. We further identify a suite of genes potentially underpinning adaptations related to thermoregulation, oxygenation, diving, vision, diet, immunity and body size, which might have facilitated their remarkable secondary transition to an aquatic ecology. Our analyses indicate that penguins and their sister group (Procellariiformes) have the lowest evolutionary rates yet detected in birds. Together, these findings help improve our understanding of how penguins have transitioned to the marine environment, successfully colonizing some of the most extreme environments on Earth.