Aerial surveys of marine mammals are routinely conducted to assess and monitor species’ habitat use and population status. In Australia, dugongs (Dugong dugon) are regularly surveyed and long-term datasets have formed the basis for defining habitat of high conservation value and risk assessments of human impacts. Unmanned aerial vehicles (UAVs) may facilitate more accurate, human-risk free, and cheaper aerial surveys. We undertook the first Australian UAV survey trial in Shark Bay, western Australia. We conducted seven flights of the ScanEagle UAV, mounted with a digital SLR camera payload. During each flight, ten transects covering a 1.3 km2 area frequently used by dugongs, were flown at 500, 750 and 1000 ft. Image (photograph) capture was controlled via the Ground Control Station and the capture rate was scheduled to achieve a prescribed 10% overlap between images along transect lines. Images were manually reviewed post hoc for animals and scored according to sun glitter, Beaufort Sea state and turbidity. We captured 6243 images, 627 containing dugongs. We also identified whales, dolphins, turtles and a range of other fauna. Of all possible dugong sightings, 95% (CI = 90%, 98%) were subjectively classed as ‘certain’ (unmistakably dugongs). Neither our dugong sighting rate, nor our ability to identify dugongs with certainty, were affected by UAV altitude. Turbidity was the only environmental variable significantly affecting the dugong sighting rate. Our results suggest that UAV systems may not be limited by sea state conditions in the same manner as sightings from manned surveys. The overlap between images proved valuable for detecting animals that were masked by sun glitter in the corners of images, and identifying animals initially captured at awkward body angles. This initial trial of a basic camera system has successfully demonstrated that the ScanEagle UAV has great potential as a tool for marine mammal aerial surveys.

Abstract. Aerial surveys are conducted for various fauna to assess abundance, distribution, and habitat use over large spatial scales. They are traditionally conducted using light aircraft with observers recording sightings in real time. Unmanned Aerial Vehicles (UAVs) offer an alternative with many potential advantages, including eliminating human risk. To be effective, this emerging platform needs to provide detection rates of animals comparable to traditional methods. UAVs can also acquire new types of information, and this new data requires a reevaluation of traditional analyses used in aerial surveys; including estimating the probability of detecting animals. We conducted 17 replicate UAV surveys of humpback whales (Megaptera novaeangliae) while simultaneously obtaining a 'census' of the population from land-based observations, to assess UAV detection probability. The ScanEagle UAV, carrying a digital SLR camera, continuously captured images (with 75% overlap) along transects covering the visual range of land-based observers. We also used ScanEagle to conduct focal follows of whale pods (n = 12, mean duration = 40 min), to assess a new method of estimating availability. A comparison of the whale detections from the UAV to the land-based census provided an estimated UAV detection probability of 0.33 (CV = 0.25; incorporating both availability and perception biases), which was not affected by environmental covariates (Beaufort sea state, glare, and cloud cover). According to our focal follows, the mean availability was 0.63 (CV = 0.37), with pods including mother/calf pairs having a higher availability (0.86, CV = 0.20) than those without (0.59, CV = 0.38). The follows also revealed (and provided a potential correction for) a downward bias in group size estimates from the UAV surveys, which resulted from asynchronous diving within whale pods, and a relatively short observation window of 9 s. We have shown that UAVs are an effective alternative to traditional methods, providing a detection probability that is within the range of previous studies for our target species. We also describe a method of assessing availability bias that represents spatial and temporal characteristics of a survey, from the same perspective as the survey platform, is benign, and provides additional data on animal behavior.

Estimating abundance of Antarctic minke whales is central to the International Whaling Commission's conservation and management work and understanding impacts of climate change on polar marine ecosystems. Detecting abundance trends is problematic, in part because minke whales are frequently sighted within Antarctic sea ice where navigational safety concerns prevent ships from surveying. Using icebreaker-supported helicopters, we conducted aerial surveys across a gradient of ice conditions to estimate minke whale density in the Weddell Sea. The surveys revealed substantial numbers of whales inside the sea ice. The Antarctic summer sea ice is undergoing rapid regional change in annual extent, distribution, and length of ice-covered season. These trends, along with substantial interannual variability in ice conditions, affect the proportion of whales available to be counted by traditional shipboard surveys. The strong association between whales and the dynamic, changing sea ice requires reexamination of the power to detect trends in whale abundance or predict ecosystem responses to climate change.

This study investigates the distribution of Antarctic minke whales (AMW) in relation to sea ice concentration and variations therein. Information on AMW densities in the sea ice‐covered parts of the Southern Ocean is required to contextualize abundance estimates obtained from circumpolar shipboard surveys in open waters, suggesting a 30% decline in AMW abundance. Conventional line‐transect shipboard surveys for density estimation are impossible in ice‐covered regions, therefore we used icebreaker‐supported helicopter surveys to obtain information on AMW densities along gradients of 0%–100% of ice concentration. We conducted five helicopter surveys in the Southern Ocean, between 2006 and 2013. Distance sampling data, satellite‐derived sea‐ice data, and bathymetric parameters were used in generalized additive models (GAMs) to produce predictions on how the density of AMWs varied over space and time, and with environmental covariates. Ice concentration, distance to the ice edge and distance from the shelf break were found to describe the distribution of AMWs. Highest densities were predicted at the ice edge and through to medium ice concentrations. Medium densities were found up to 500 km into the ice edge in all concentrations of ice. Very low numbers of AMWs were found in the ice‐free waters of the West Antarctic Peninsula (WAP). A consistent relationship between AMW distribution and sea ice concentration weakens the support for the hypothesis that varying numbers of AMWs in ice‐covered waters were responsible for observed changes in estimated abundance. The potential decline in AMW abundance stresses the need for conservation measures and further studies into the AMW population status. Very low numbers of AMWs recorded in the ice‐free waters along the WAP support the hypothesis that this species is strongly dependent on sea ice and that forecasted sea ice changes have the potential of heavily impacting AMWs.

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Around 176500 whales were killed in the sub-Antarctic waters off South Georgia (South Atlantic) between 1904 and 1965. In recent decades, whales have once again become summer visitors, with the southern right whale (SRW) the most commonly reported species until 2011. Here, we assess the distribution, temporal pattern, health status and likely prey of SRWs in these waters, combining observations from a summertime vessel-based expedition to South Georgia, stable isotope data collected from SRWs and putative prey and sightings reports collated by the South Georgia Museum. The expedition used directional acoustics and visual surveys to localise whales and collected skin biopsies and photo-IDs. During 76 h of visual observation effort over 19 expedition days, SRWs were encountered 15 times (~31 individuals). Photo-IDs, combined with publicly contributed images from commercial vessels, were reconciled and quality-controlled to form a catalogue of 6 fully (i.e. both sides) identified SRWs and 26 SRWs identified by either left or right sides. No photo-ID matches were found with lower-latitude calving grounds, but 3 whales had gull lesions supporting a direct link with Península Valdés, Argentina. The isotopic position of SRWs in the South Georgia food web suggests feeding on a combination of copepod and krill species. Opportunistic reports of SRW sightings and associated group sizes remain steady over time, while humpback whales provide a strong contrast, with increased sighting rates and group sizes seen since 2013. These data suggest a plateau in SRWs and an increasing humpback whale presence in South Georgia waters following the cessation of whaling.

Following the cessation of whaling, South Atlantic populations of humpback Megaptera novaeangliae and some other baleen whale species are recovering, but there has been limited monitoring of their recovery in the Scotia Arc, a former whaling epicentre and a hotspot for Antarctic krill Euphausia superba. To inform the management of krill fisheries, up-to-date assessment of whale biomass and prey consumption is essential. Using a model-based approach, we provide the first estimates of whale abundance and krill consumption for South Georgia and the South Sandwich Islands and total abundance of humpback whales across their southwestern Atlantic feeding grounds, using data collected in 2019. Humpback whale abundance was estimated at 24543 (coefficient of variation, CV = 0.26; 95% CI = 14863-40528), similar to that measured in Brazil on the main wintering ground for this population. The abundance of baleen whales in South Georgia and the South Sandwich Islands, including those not identified to species level, was estimated at 43824 (CV = 0.15, 95% CI = 33509-59077). Based on the proportion of humpback whales identified during the surveys (83%), the majority of these are likely to be humpback whales. Annual krill consumption by baleen whales was estimated to be in the range 4.8 to 7.2 million tons, representing 7 to 10% of the estimated krill biomass in the region. However, there is a need to better understand feeding rates in baleen whales, and further research into this field should be a priority to improve the accuracy and precision of prey consumption rate estimation.

As whales recover from commercial exploitation, they are increasing in abundance in habitats that they have been absent from for decades. However, studying the recovery and habitat use patterns of whales, particularly in remote and inaccessible regions, frequently poses logistical and economic challenges. Here we trial a new approach for measuring whale density in a remote area, using Very-High-Resolution WorldView-3 satellite imagery. This approach has capacity to provide sightings data to complement and assist traditional sightings surveys. We compare at-sea whale density estimates to estimates derived from satellite imagery collected at a similar time, and use suction-cup archival logger data to make an adjustment for surface availability. We demonstrate that satellite imagery can provide useful data on whale occurrence and density. Densities, when unadjusted for surface availability are shown to be considerably lower than those estimated by the ship survey. However, adjusted for surface availability and weather conditions (0.13 whales per km 2 , CV = 0.38), they fall within an order of magnitude of those derived by traditional line-transect estimates (0.33 whales per km 2 , CV = 0.09). Satellite surveys represent an exciting development for high-resolution image-based cetacean observation at sea, particularly in inaccessible regions, presenting opportunities for ongoing and future research. Gathering data on cetacean distribution and densities has traditionally employed visual observers operating from various platforms, typically either ships, aircraft or land 1-5. Much of our understanding about baleen whale population recovery and ecology depends on these methods 6-8. In oceanic regions close to population centres, these methods are often used to monitor regional population densities 8-10. However, regular applications of these methods are often constrained in remote, inaccessible regions, where their use represents a significant logistical and financial commitment 11. Consequently, such surveys are infrequent, making monitoring of population trends more challenging. In the Southern Ocean, the only comprehensive surveys south of 60° S (i.e. the putative summer foraging area for a range of cetacean species) were those undertaken by the International Whaling Commission (IWC) during the International Decade of Cetacean Research and the Southern Ocean Whale Ecosystem Research (IDCR SOWER) surveys, between 1978/9 and 2003/4. These surveys circumnavigated the continent three times, and based on these data Southern Ocean baleen whale recovery trends have been estimated 6,12,13. However, smallscale, sometimes ad hoc studies are far more common. These are generally biased towards the most accessible regions of the Southern Ocean 14 , the Western Antarctic Peninsula 3,4,15-18 , with more limited studies also conducted in the Scotia Arc 19 , Weddell Sea 20 and limited areas of East Antarctica 21,22. The Southern Ocean represents