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Our aim was to estimate the population of emperor penguins (Aptenodytes fosteri) using a single synoptic survey. We examined the whole continental coastline of Antarctica using a combination of medium resolution and Very High Resolution (VHR) satellite imagery to identify emperor penguin colony locations. Where colonies were identified, VHR imagery was obtained in the 2009 breeding season. The remotely-sensed images were then analysed using a supervised classification method to separate penguins from snow, shadow and guano. Actual counts of penguins from eleven ground truthing sites were used to convert these classified areas into numbers of penguins using a robust regression algorithm.We found four new colonies and confirmed the location of three previously suspected sites giving a total number of emperor penguin breeding colonies of 46. We estimated the breeding population of emperor penguins at each colony during 2009 and provide a population estimate of ~238,000 breeding pairs (compared with the last previously published count of 135,000-175,000 pairs). Based on published values of the relationship between breeders and non-breeders, this translates to a total population of ~595,000 adult birds.There is a growing consensus in the literature that global and regional emperor penguin populations will be affected by changing climate, a driver thought to be critical to their future survival. However, a complete understanding is severely limited by the lack of detailed knowledge about much of their ecology, and importantly a poor understanding of their total breeding population. To address the second of these issues, our work now provides a comprehensive estimate of the total breeding population that can be used in future population models and will provide a baseline for long-term research.

Emperor penguins ( Aptenodytes forsteri ) are under increasing environmental pressure. Monitoring colony size and population trends of this Antarctic seabird relies primarily on satellite imagery recorded near the end of the breeding season, when light conditions levels are sufficient to capture images, but colony occupancy is highly variable. To correct population estimates for this variability, we develop a phenological model that can predict the number of breeding pairs and fledging chicks, as well as key phenological events such as arrival, hatching and foraging times, from as few as six data points from a single season. The ability to extrapolate occupancy from sparse data makes the model particularly useful for monitoring remotely sensed animal colonies where ground-based population estimates are rare or unavailable. Emperor penguins colony occupancy is variable and chiefly estimated with remote sensing images at end of the breeding season. Here, the authors provide a phenological model that can extrapolate occupancy from sparse data and can predict phenological events, breeding pairs and fledging chicks.

The correct sitting posture in a wheelchair is crucial for paralyzed people. This helps prevent problems such as pressure ulcers, muscle contractures, and respiratory problems. A paralyzed person with poor sitting posture is highly likely to slip out of their wheelchair. To prevent this from happening and consistently maintain paralyzed individuals under observation, a new model, the Emperor Penguin Optimized Sensor-Infused Wheelchair (EPIC), has been designed to monitor the position and health of the individual in the wheelchair in real-time. A Force Sensitive Resistor (FSR) sensor and an ultrasonic sensor continuously transmit information to the Arduino UNO R4 Wi-Fi board. The Emperor Penguin Optimizer Algorithm (EPOA) was used to select the features sent from the Arduino board to the ESP8266-Wi-Fi module. A Deep Maxout Network (DMN) was used to predict the posture of a wheelchair-using patient following the feature selection phase. A mobile application for Android collects data from the ESP32 module and estimates posture to inform the caretaker about the user’s current posture and health status. Evaluation metrics such as precision, accuracy, sensitivity, and specificity have been used to determine the efficiency in the EPIC framework, which improves overall accuracy by 10.1%, 7.73%, and 2.84% for better posture recognition.

Weddell seal Leptonychotes weddellii populations can potentially serve as indicators of change in Southern Ocean food web structure, but tracking populations at regional to continental scales has so far been impossible. Here, we combined citizen science with remote sensing to learn about environmental and biological factors that explain fine-scale distribution of Weddell seal haul-outs in the Ross Sea, Antarctica. We employed the crowd-sourcing platform Tomnod (DigitalGlobe) to host high-resolution (~0.5–0.6 m) satellite imagery of the Antarctic fast ice during November in 2010 and 2011 and asked volunteers to identify seals on images. We created a 5 km × 5 km grid of seal presence per year, and modeled habitat suitability for seals using a generalized linear model. The top Ross Sea-wide model that best explained seal presence included proximity to fast-ice cracks, deep water, and emperor penguin Aptenodytes forsteri colonies. This model also revealed that seal presence decreased with proximity to Adélie penguin Pygoscelis adeliae colonies and size of the nearest emperor penguin colony, suggesting the potential for trophic competitive exclusion by large penguin colonies. With respect to 3 sub-regions within the Ross Sea (North and South Victoria Land in the western Ross Sea, and Marie Byrd Land in the east), we found that 3 habitat variables differed in their effects among sub-regions: proximity to emperor penguin colonies, proximity to deep water, and relative ice width. Our results represent a step toward effectively monitoring Weddell seal population trends, and disentangling biological and environmental factors influencing locations of Weddell seal haul-outs around Antarctica.

An increasing number of marine animals are equipped with biologgers, to study their physiology, behaviour and ecology, often for conservation purposes. To minimise the impacts of biologgers on the animals’ welfare, the Refinement principle from the Three Rs framework ( Replacement , Reduction , Refinement ) urges to continuously test and evaluate new and updated biologging protocols. Here, we propose alternative and promising techniques for emperor penguin ( Aptenodytes forsteri ) capture and on-site logger deployment that aim to mitigate the potential negative impacts of logger deployment on these birds. We equipped adult emperor penguins for short-term (GPS, Time-Depth Recorder (TDR)) and long-term ( i . e . planned for one year) deployments (ARGOS platforms, TDR), as well as juvenile emperor penguins for long-term deployments (ARGOS platforms) in the Weddell Sea area where they had not yet been studied. We describe and qualitatively evaluate our protocols for the attachment of biologgers on-site at the colony, the capture of the animals and the recovery of the devices after deployment. We report unprecedented recaptures of long-term equipped adult emperor penguins (50% of equipped individuals recaptured after 290 days). Our data demonstrate that the traditional technique of long-term attachment by gluing the biologgers directly to the back feathers causes excessive feather breakage and the loss of the devices after a few months. We therefore propose an alternative method of attachment for back-mounted devices. This technique led to successful year-round deployments on 37.5% of the equipped juveniles. Finally, we also disclose the first deployments of leg-bracelet mounted TDRs on emperor penguins. Our findings highlight the importance of monitoring potential impacts of biologger deployments on the animals and the need to continue to improve methods to minimize disturbance and enhance performance and results.

To adapt to habitat temperature, vertebrates have developed sophisticated physiological and ecological mechanisms through evolution. Transient receptor potential melastatin 8 (TRPM8) serves as the primary sensor for cold. However, how cold activates TRPM8 and how this sensor is tuned for thermal adaptation remain largely unknown. Here we established a molecular framework of how cold is sensed in TRPM8 with a combination of patch-clamp recording, unnatural amino acid imaging, and structural modeling. We first observed that the maximum cold activation of TRPM8 in eight different vertebrates (i.e., African elephant and emperor penguin) with distinct side-chain hydrophobicity (SCH) in the pore domain (PD) is tuned to match their habitat temperature. We further showed that altering SCH for residues in the PD with solvent-accessibility changes leads to specific tuning of the cold response in TRPM8. We also observed that knockin mice expressing the penguin's TRPM8 exhibited remarkable tolerance to cold. Together, our findings suggest a paradigm of thermal adaptation in vertebrates, where the evolutionary tuning of the cold activation in the TRPM8 ion channel through altering SCH and solvent accessibility in its PD largely contributes to the setting of the cold-sensitive/tolerant phenotype.

Many ecological systems dominated by stochastic dynamics can produce complex time series that inherently limit forecast accuracy. The ‘intrinsic predictability’ of these systems can be approximated by a time series complexity metric called weighted permutation entropy (WPE). While WPE is a useful metric to gauge forecast performance prior to model building, it is sensitive to noise and may be biased depending on the length of the time series. Here, we introduce a simple randomized permutation test (rWPE) to assess whether a time series is intrinsically more predictable than white noise. We apply rWPE to both simulated and empirical data to assess its performance and usefulness. To do this, we simulate population dynamics under various scenarios, including a linear trend, chaotic, periodic and equilibrium dynamics. We further test this approach with observed abundance time series for 932 species across four orders of animals from the Global Population Dynamics Database. Finally, using Adélie (Pygoscelis adeliae) and emperor penguin (Aptenodytes forsteri) time series as case studies, we demonstrate the application of rWPE to multiple populations for a single species. We show that rWPE can determine whether a system is significantly more predictable than white noise, even with time series as short as 10 years that show an apparent trend under biologically realistic stochasticity levels. Additionally, rWPE has statistical power close to 100% when time series are at least 30 time steps long and show chaotic or periodic dynamics. Power decreases to ~10% under equilibrium dynamics, irrespective of time series length. Among four classes of animal taxa, mammals have the highest relative frequency (28%) of time series that are both longer than 30 time steps and indistinguishable from white noise in terms of complexity, followed by insects (16%), birds (16%) and bony fishes (11%). rWPE is a straightforward and useful method widely applicable to any time series, including short ones. By informing forecasters of the inherent limitations to a system's predictability, it can guide a modeller's expectations for forecast performance.

Large animals such as sea birds and marine mammals can transport limiting nutrients between different regions of the ocean, thereby stimulating and enhancing productivity. In Antarctica this process is influenced by formation and breakup of sea ice and its influence on the feeding behaviour of predators and their prey. We used analyses of bioactive metals (for example, Fe, Co, Mn), macronutrients (for example, N) and stable isotopes (δ¹³C and δ¹⁵N) in the excreta of Adélie (Pygoscelis adeliae) and emperor penguins (Aptenodytes forsteri) as well as Weddell seals (Leptonychotes weddellii) from multiple sites, among multiple years (2012–2014) to resolve how changes in sea ice dynamics, as indicated by MODIS satellite images, were coincident with prey switching and likely changes in nutrient fluxes between the offshore pelagic and coastal zones. We also sampled excreta of the south polar skua (Stercorarius maccormicki), which preys on penguins and scavenges the remains of both penguins and seals. We found strong coincidence of isotopic evidence for prey switching, between euphausiids (Euphausia superba and E. crystallorophias) and pelagic/cryopelagic fishes (for example, Pleuragramma antarcticum) in penguins, and between pelagic/cryopelagic fishes and Antarctic toothfish (Dissostichus mawsoni) in Weddell seals, with changes in sea ice cover among years. Further, prey switching was strongly linked to changes in the concentrations of nutrients (Fe and N) deposited in coastal environments by both penguins and seals. Our findings have important implications for understanding how the roles of large animals in supporting coastal productivity may shift with environmental conditions in polar ecosystems.

Transient stability preventive control (TSPC), a method to efficiently withstand the severe contingencies in a power system, is mathematically a transient stability constrained optimal power flow (TSC-OPF) issue, attempting to maintain the economical and secure dispatch of a power system via generation rescheduling. The traditional TSC-OPF issue incorporated with differential-algebraic equations (DAE) is time consumption and difficult to solve. Therefore, this paper proposes a new TSPC method driven by a naturally inspired optimization algorithm integrated with transient stability assessment. To avoid solving complex DAE, the stacking ensemble multilayer perceptron (SEMLP) is used in this research as a transient stability assessment (TSA) model and integrated into the optimization algorithm to replace transient stability constraints. Therefore, less time is spent on challenging calculations. Simultaneously, sensitivity analysis (SA) based on this TSA model determines the adjustment direction of the controllable generators set. The results of this SA can be utilized as prior knowledge for subsequent optimization algorithms, thus further reducing the time consumption process. In addition, a naturally inspired algorithm, Aptenodytes Forsteri Optimization (AFO), is introduced to find the best operating point with a near-optimal operational cost while ensuring power system stability. The accuracy and effectiveness of the method are verified on the IEEE 39-bus system and the IEEE 300-bus system. After the implementation of the proposed TSPC method, both systems can ensure transient stability under a given contingency. The test experiment using AFO driven by SEMLP and SA on the IEEE 39-bus system is completed in about 35 s, which is one-tenth of the time required by the time domain simulation method.

We assess the response of pack ice penguins, Emperor (Aptenodytes forsteri) and Adelie (Pygoscelis adeliae), to habitat variability and, then, by modeling habitat alterations, the qualitative changes to their populations, size and distribution, as Earth's average tropospheric temperature reaches 2C above preindustrial levels (ca. 1860), the benchmark set by the European Union in efforts to reduce greenhouse gases. First, we assessed models used in the Intergovernmental Panel on Climate Change Fourth Assessment Report (AR4) on penguin performance duplicating existing conditions in the Southern Ocean. We chose four models appropriate for gauging changes to penguin habitat: GFDL-CM2.1, GFDL-CM2.0, MIROC3.2(hi-res), and MRI-CGCM2.3.2a. Second, we analyzed the composited model ENSEMBLE to estimate the point of 2C warming (2025-2052) and the projected changes to sea ice coverage (extent, persistence, and concentration), sea ice thickness, wind speeds, precipitation, and air temperatures. Third, we considered studies of ancient colonies and sediment cores and some recent modeling, which indicate the (space/time) large/centennial-scale penguin response to habitat limits of all ice or no ice. Then we considered results of statistical modeling at the temporal interannual-decadal scale in regard to penguin response over a continuum of rather complex, meso- to large-scale habitat conditions, some of which have opposing and others interacting effects. The ENSEMBLE meso/decadal-scale output projects a marked narrowing of penguins' zoogeographic range at the 2C point. Colonies north of 70 S are projected to decrease or disappear: 650% of Emperor colonies (40% of breeding population) and 675% of Adelie colonies (70% of breeding population), but limited growth might occur south of 73 S. Net change would result largely from positive responses to increase in polynya persistence at high latitudes, overcome by decreases in pack ice cover at lower latitudes and, particularly for Emperors, ice thickness. Adelie Penguins might colonize new breeding habitat where concentrated pack ice diverges and/or disintegrating ice shelves expose coastline. Limiting increase will be decreased persistence of pack ice north of the Antarctic Circle, as this species requires daylight in its wintering areas. Adelies would be affected negatively by increasing snowfall, predicted to increase in certain areas owing to intrusions of warm, moist marine air due to changes in the Polar Jet Stream.