The most problematic issue in the ocean color application is the presence of heavy clouds, especially in polar regions. For that reason, the demand for the ocean color application in polar regions is increased. As a way to overcome such issues, we conducted the reconstruction of the chlorophyll-a concentration (CHL) data using the machine learning-based models to raise the usability of CHL data. This analysis was first conducted on a regional scale and focused on the biologically-valued Cape Hallett, Ross Sea, Antarctica. Environmental factors and geographical information associated with phytoplankton dynamics were considered as predictors for the CHL reconstruction, which were obtained from cloud-free microwave and reanalysis data. As the machine learning models used in the present study, the ensemble-based models such as Random forest (RF) and Extremely randomized tree (ET) were selected with 10-fold cross-validation. As a result, both CHL reconstructions from the two models showed significant agreement with the standard satellite-derived CHL data. In addition, the reconstructed CHLs were close to the actual CHL value even where it was not observed by the satellites. However, there is a slight difference between the CHL reconstruction results from the RF and the ET, which is likely caused by the difference in the contribution of each predictor. In addition, we examined the variable importance for the CHL reconstruction quantitatively. As such, the sea surface and atmospheric temperature, and the photosynthetically available radiation have high contributions to the model developments. Mostly, geographic information appears to have a lower contribution relative to environmental predictors. Lastly, we estimated the partial dependences for the predictors for further study on the variable contribution and investigated the contributions to the CHL reconstruction with changes in the predictors.

Ecosystem dynamics at the northwest Antarctic Peninsula are driven by interactions between physical and biological processes. For example, baleen whale populations are recovering from commercial harvesting against the backdrop of rapid climate change, including reduced sea ice extent and changing ecosystem composition. Concurrently, the commercial harvesting of Antarctic krill is increasing, with the potential to increase the likelihood for competition with and between krill predators and the fishery. However, understanding the ecology, abundance, and spatial distribution of krill predators is often limited, outdated, or at spatial scales that do not match those desired for effective fisheries management. We update current knowledge of predator dependence on krill by integrating telemetry‐based data, at‐sea observational surveys, estimates of predator abundance, and physiological data to estimate the spatial distribution of krill consumption during the austral summer by three species ofPygoscelispenguin, 11 species of flying seabirds, one species of pinniped, and two species of baleen whale. Our models show that the majority of important areas for krill predator foraging are close to penguin breeding colonies in nearshore areas where humpback whales also regularly feed, and along the shelf‐break, though we caution that not all known krill predators are included in these analyses. We show that krill consumption is highly variable across the region, and often concentrated at fine spatial scales, emphasizing the need for the management of the local krill fishery at relevant temporal and spatial scales. We also note that krill consumption by recovering populations of krill predators provides further evidence in support of the krill surplus hypothesis, and highlight that despite less than comprehensive data, cetaceans are likely to consume a significant proportion of the krill consumed by natural predators but are not currently considered directly in the management of the krill fishery. If management of the krill fishery is to be precautionary and operate in a way that minimizes the risks to krill predator populations, it will be necessary in future analyses, to include up‐to‐date and precise abundance and consumption estimates for pack‐ice seals, finfish, squid, and other baleen whale species not currently considered.

Adenoviruses (family Adenoviridae) infect various organ systems and cause diseases in a wide range of host species. In this study, we examined multiple tissues from Chinstrap penguins (Pygoscelis antarctica), collected in Antarctica during 2009 and 2010, for the presence of novel adenoviruses by PCR. Analysis of a 855-bp region of the hexon gene of a newly identified adenovirus, designated Chinstrap penguin adenovirus 1 (CSPAdV-1), showed nucleotide (amino acid) sequence identity of 71.8% (65.5%) with South Polar skua 1 (SPSAdV-1), 71% (70%) with raptor adenovirus 1 (RAdV-1), 71.4% (67.6%) with turkey adenovirus 3 (TAdV-3) and 61% (61.6%) with frog adenovirus 1 (FrAdV-1). Based on the genetic and phylogenetic analyses, CSPAdV-1 was classified as a member of the genus, Siadenovirus. Virus isolation attempts from kidney homogenates in the MDTC-RP19 (ATCC® CRL-8135™) cell line were unsuccessful. In conclusion, this study provides the first evidence of new adenovirus species in Antarctic penguins.

Aim: To provide a method of analyzing penguin tracking data to identify priority at‐sea areas for seabird conservation (marine IBAs), based on pre‐existing approaches for flying seabirds but revised according to the specific ecology of Pygoscelis penguin species.Location: Waters around the Antarctic Peninsula, South Shetland, and South Orkney archipelagos (FAO Subareas 48.1 and 48.2).Methods: We made key improvements to the pre‐existing protocol for identifying marine IBAs that include refining the track interpolation method and revision of parameters for the kernel analysis (smoothing factor and utilization distribution) using sensitivity tests. We applied the revised method to 24 datasets of tracking data on penguins (three species, seven colonies, and three different breeding stages—incubation, brood, and crèche).Results: We identified five new marine IBAs for seabirds in the study area, estimated to hold ca. 600,000 adult penguins.Main conclusions: The results demonstrate the efficacy of a new method for the designation of a network of marine IBAs in Antarctic waters for penguins based on tracking data, which can contribute to an evidence‐based, precautionary, management framework for krill fisheries.

The diet of Adélie penguins, Pygoscelis adeliae, is a useful indicator in understanding the ecological conditions of their habitats. The diets of Adélie penguins were studied using metabarcoding and quantitative PCR (qPCR) analyses of fecal DNA from seven habitats along the Ross Sea region. Using metabarcoding analysis with dual universal primers (18Sv9 and miniFish), the overall diet composition and detailed information about piscine prey were clearly elucidated. It was found that two krill species (Euphausia superba and Euphausia crystallorophias) and notothenioid fish were the most abundant in the diets of Adélie penguins. Among the notothenioid prey, Pleuragramma antarctica (56.50%) and Pagothenia borchgrevinki (18.21%) were the two most abundant species. qPCR analysis showed a significant geographic difference in the composition of main prey. Penguins inhabiting outbound parts of the Ross Sea (Capes Adare (CA) and Duke of York Island (DY)) mainly preyed on E. superba, without any significant changes in prey composition. By contrast, those inhabiting the inbound parts of the Ross Sea (Edmonson Point (EP) and Inexpressible Island (II)) preyed on E. crystallorophias and notothenioid fish rather than E. superba. Compared with the outbound habitats, prey compositions for penguins inhabiting the inbound regions were significantly different year to year, which was presumably due to the food availability based on the annual environmental and meteorological conditions of the coastal region along with the inbound parts of the Ross Sea.

Theory predicts that sympatric predators compete for food under conditions of limited resources. Competition would occur even within the same species, between neighboring populations, because of overlapping foraging habits. Thus, neighboring populations of the same species are hypothesized to face strong competition. To test the hypothesis that intra-specific competition is more intense than inter-specific competition owing to a lack of niche partitioning, we estimated the foraging area and diving depths of two colonial seabird species at two neighboring colonies. Using GPS and time-depth recorders, we tracked foraging space use of sympatric breeding Chinstrap and Gentoo penguins at Ardley Island (AI) and Narębski Point (NP) at King George Island, Antarctica. GPS tracks showed that there was a larger overlap in the foraging areas between the two species than within each species. In dive parameters, Gentoo penguins performed deeper and longer dives than Chinstrap penguins at the same colonies. At the colony level, Gentoo penguins from NP undertook deeper and longer dives than those at AI, whereas Chinstrap penguins did not show such intra-specific differences in dives. Stable isotope analysis of δ¹³C and δ¹⁵N isotopes in blood demonstrated both inter- and intra-specific differences. Both species of penguin at AI exhibited higher δ¹³C and δ¹⁵N values than those at NP, and in both locations, Gentoo penguins had higher δ¹³C and lower δ¹⁵N values than Chinstrap penguins. Isotopic niches showed that there were lower inter-specific overlaps than intra-specific overlaps. This suggests that, despite the low intra-specific spatial overlap, diets of conspecifics from different colonies remained more similar, resulting in the higher isotopic niche overlaps. Collectively, our results support the hypothesis that intra-specific competition is higher than inter-specific competition, leading to spatial segregation of the neighboring populations of the same species.