Explore the vast range of titles available.

Antarctic krill Euphausia superba, a keystone species in the Southern Ocean, is highly relevant for studying effects of climate-related shifts on management systems. Krill provides a key link between primary producers and higher trophic levels and supports the largest regional fishery. Any major perturbation in the krill population would have severe ecological and economic ramifications. We review the literature to determine how climate change, in concert with other environmental changes, alters krill habitat, affects spatial distribution/abundance, and impacts fisheries management. Findings recently reported on the effects of climate change on krill distribution and abundance are inconsistent, however, raising questions regarding methods used to detect changes in density and biomass. One recent study reported a sharp decline in krill densities near their northern limit, accompanied by a poleward contraction in distribution in the Southwest Atlantic sector. Another recent study found no evidence of long-term decline in krill density or biomass and reported no evidence of a poleward shift in distribution. Moreover, with predicted decreases in phytoplankton production, vertical foraging migrations to the seabed may become more frequent, also impacting krill production and harvesting. Potentially cumulative impacts of climate change further compound the management challenge faced by CCAMLR, the organization responsible for conservation of Antarctic marine living resources: to detect changes in the abundance, distribution, and reproductive performance of krill and krill-dependent predator stocks and to respond to such change by adjusting its conservation measures. Based on CCAMLR reports and documents, we review the institutional framework, outline how climate change has been addressed within this organization, and examine the prospects for further advances toward ecosystem risk assessment and an adaptive management system.

Understanding how an animal utilises its surroundings requires its movements through space to be described accurately. Satellite telemetry is the only means of acquiring movement data for many species however data are prone to varying amounts of spatial error; the recent application of state-space models (SSMs) to the location estimation problem have provided a means to incorporate spatial errors when characterising animal movements. The predominant platform for collecting satellite telemetry data on free-ranging animals, Service Argos, recently provided an alternative Doppler location estimation algorithm that is purported to be more accurate and generate a greater number of locations that its predecessor. We provide a comprehensive assessment of this new estimation process performance on data from free-ranging animals relative to concurrently collected Fastloc GPS data. Additionally, we test the efficacy of three readily-available SSM in predicting the movement of two focal animals. Raw Argos location estimates generated by the new algorithm were greatly improved compared to the old system. Approximately twice as many Argos locations were derived compared to GPS on the devices used. Root Mean Square Errors (RMSE) for each optimal SSM were less than 4.25 km with some producing RMSE of less than 2.50 km. Differences in the biological plausibility of the tracks between the two focal animals used to investigate the utility of SSM highlights the importance of considering animal behaviour in movement studies. The ability to reprocess Argos data collected since 2008 with the new algorithm should permit questions of animal movement to be revisited at a finer resolution.

Animal‐attached devices, or bio‐loggers, that record data on multiple channels are frequently used to study the movement of free‐ranging animals. In recent years, the deployment of animal‐borne video cameras in addition to other time‐series loggers, such as accelerometers and depth sensors, has become popular. Visual observations from animal‐borne cameras provide ideal ground‐truth data when behavioural inferences are made from concurrently deployed bio‐loggers. However, such deployments generate large amounts of data that are often not synchronised and may be difficult to analyse because open‐source software tools facilitating simultaneous visualisation of multiple data channels along with video streams are lacking. Here we present VANTAGE (Video Analysis and Navigation Tool for Advanced Graphical Exploration, available at https://github.com/sschoombie/VANTAGE), a new open‐source graphical user interface written in Python. VANTAGE aims to simplify time‐consuming data processing and analyses through (1) concurrent visualisation of video footage and accompanying bio‐logger time‐series data, (2) temporal synchronisation of the different data streams, (3) efficient annotation across data types, and (4) video enhancement and machine learning functionalities. We illustrate both manual and automated synchronisation of animal‐borne video and accelerometer‐depth data (obtained from foraging penguins) using VANTAGE. Once synchronised, VANTAGE allows for quick and easy navigation through the data to areas of interest, with behavioural observations labelled on one data type reflecting in all the data series. The labelled time‐series data can then be exported for further analyses (e.g., in machine learning applications). VANTAGE allows the integration of video and other time‐series data recorded at the same time, allowing more efficient analysis and labelling of the data. Bio‐logging studies often use data from multiple loggers, and analysing these data can be challenging when not properly synchronised. VANTAGE aims to simplify this synchronisation process through visualisation of multiple data streams.

The southern coastline of Australia forms part of the worlds' only northern boundary current system. The Bonney Upwelling occurs every austral summer along the south-eastern South Australian coastline, a region that hosts over 80% of the worlds population of an endangered endemic otariid, the Australian sea lion. We present the first data on the movement characteristics and foraging behaviour of adult male Australian sea lions across their South Australian range. Synthesizing telemetric, oceanographic and isotopic datasets collected from seven individuals enabled us to characterise individual foraging behaviour over an approximate two year time period. Data suggested seasonal variability in stable carbon and nitrogen isotopes that could not be otherwise explained by changes in animal movement patterns. Similarly, animals did not change their foraging patterns despite fine-scale spatial and temporal variability of the upwelling event. Individual males tended to return to the same colony at which they were tagged and utilized the same at-sea regions for foraging irrespective of oceanographic conditions or time of year. Our study contrasts current general assumptions that male otariid life history strategies should result in greater dispersal, with adult male Australian sea lions displaying central place foraging behaviour similar to males of other otariid species in the region.

Monitored seabird populations—useful sentinels of marine ecosystem health—have been declining worldwide at a rapid pace. Yet, lack of reliable long-term monitoring data constrains assessment of the conservation status of many seabird populations. Unmanned aerial vehicles (UAVs) have the potential to increase survey efficiency and count precision of seabird populations, especially where time constraints or inaccessible terrain, such as sea stacks, limit meaningful ground-based surveys. Furthermore, tremendous potential exists to combine fine-scale spatially integrated habitat mapping obtained from UAV images with occupancy to unravel how abiotic factors such as topography affect animal populations. In late December 2018, we used an UAV to create a georeferenced orthomosaic image and digital elevation model (DEM) from which we determined the size of the Antarctic shag (Leucocarbo bransfieldensis) breeding colony at Harmony Point, Nelson Island, South Shetland Islands. Our population estimate of 69 breeding pairs is approximately double that reported for the early 2000s and the highest count since the late 1980s. Most nests were located 10 to 20 m above sea level, on relatively shallow gradients that predominantly faced southeast. While it is difficult to compare historical ground-based counts with the UAV-derived estimates presented here, our new data provide robust baseline information for future monitoring of the colony population size using comparable survey methods. Our basic mapping of the topography of the breeding colony also highlights how UAV-derived habitat information can facilitate our understanding of the influence of landscape structure on animal population dynamics.

Aim To predict the at‐sea distribution of chinstrap penguins across the South Orkney Islands and to quantify the overlap with the Southern Ocean krill fishery. Location South Orkney Islands, Antarctica. Methods Penguins from four colonies across the South Orkney Islands were tracked using global positioning systems (GPSs) and time depth recorders (TDRs). Relationships between a variety of environmental and geometric variables and the at‐sea distribution of penguins were investigated using general additive models for the three main phases of the breeding season. Subsequently, the final models were extrapolated across the South Orkney archipelago to predict the at‐sea distribution of penguins from colonies where no tracking data are available. Finally, the overlap between areas used by chinstrap penguins and the krill fishery was quantified. Results The foraging distribution of chinstrap penguins can be predicted using two simple and static variables: the distance from the colony and the direction of travel towards the shelf‐edge, while avoiding high densities of Pygoscelis penguins from other colonies. Additionally, we find that the chinstrap penguins breeding on the South Orkney Islands use areas which overlap with frequently used krill fishing areas and that this overlap is most prominent during the brood and crèche phases of the breeding season. Main conclusions This is the first step in understanding the potential impacts of the krill fishery, for all colonies including those where no empirical tracking data are available. However, with the available data, it is not currently possible to infer an impact of the krill fisheries on penguins. With this in mind, we recommend the implementation of monitoring schemes to investigate the effects of prey depletion on predator populations and to ensure that management continues to follow a precautionary approach and is addressed at spatial and temporal scales relevant to ecosystem operation.

Many populations of southern hemisphere baleen whales are recovering and are again becoming dominant consumers in the Southern Ocean. Key to understanding the present and future role of baleen whales in Southern Ocean ecosystems is determining their abundance on foraging grounds. Distance sampling is the standard method for estimating baleen whale abundance but requires specific logistic requirements which are rarely achieved in the remote Southern Ocean. We explore the potential use of tourist vessel-based sampling as a cost-effective solution for conducting distance sampling surveys for baleen whales in the Southern Ocean. We used a dataset of tourist vessel locations from the southwest Atlantic sector of the Southern Ocean and published knowledge from Southern Ocean sighting surveys to determine the number of tourist vessel voyages required for robust abundance estimates. Second, we simulated the abundance and distributions of four baleen whale species for the study area and sampled them with both standardized line transect surveys and non-standardized tourist vessel-based surveys, then compared modeled abundance and distributions from each survey to the original simulation. For the southwest Atlantic, we show that 12-22 tourist vessel voyages are likely required to estimate abundance for humpback and fin whales, with relative estimates for blue, sei, Antarctic minke, and southern right whales. Second, we show tourist vessel-based surveys outperformed standardized line transect surveys at reproducing simulated baleen whale abundances and distribution. These analyses suggest tourist vessel-based surveys are a viable method for estimating baleen whale abundance in remote regions. For the southwest Atlantic, the relatively cost-effective nature of tourist vessel-based survey and regularity of tourist vessel voyages could allow for annual and intra-annual estimates of abundance, a fundamental improvement on current methods, which may capture spatiotemporal trends in baleen whale movements on forging grounds. Comparative modeling of sampling methods provided insights into the behavior of general additive model-based abundance modeling, contributing to the development of detailed guidelines of best practices for these approaches. Through successful engagement with tourist company partners, this method has the potential to characterize abundance across a variety of marine species and spaces globally, and deliver high-quality scientific outcomes relevant to management organizations.

Marine predators are integral to the functioning of marine ecosystems, and their consumption requirements should be integrated into ecosystem-based management policies. However, estimating prey consumption in diving marine predators requires innovative methods as predator–prey interactions are rarely observable. We developed a novel method, validated by animal-borne video, that uses tri-axial acceleration and depth data to quantify prey capture rates in chinstrap penguins ( Pygoscelis antarctica ). These penguins are important consumers of Antarctic krill ( Euphausia superba ), a commercially harvested crustacean central to the Southern Ocean food web. We collected a large data set ( n = 41 individuals) comprising overlapping video, accelerometer and depth data from foraging penguins. Prey captures were manually identified in videos, and those observations were used in supervised training of two deep learning neural networks (convolutional neural network (CNN) and V-Net). Although the CNN and V-Net architectures and input data pipelines differed, both trained models were able to predict prey captures from new acceleration and depth data (linear regression slope of predictions against video-observed prey captures = 1.13; R 2 ≈ 0.86). Our results illustrate that deep learning algorithms offer a means to process the large quantities of data generated by contemporary bio-logging sensors to robustly estimate prey capture events in diving marine predators.

Recent influxes of warm Atlantic water into the fjords of west Spitsbergen have led to concomitant influx of more temperate and boreal fish species. The changes in the water masses within the fjords naturally affect all trophic levels of the sympagic, benthic, and pelagic food chains in the area. The most abundant marine mammal species in the fjords of west Spitsbergen is the ringed seal ( Pusa hispida ), which feeds, breeds, and moults in this area. In this study, we used isotopic data from whiskers of two cohorts of adult ringed seals (sampled in 1990 and 2013) to determine whether signals of ecosystem changes were detectable in this top marine predator. Acknowledging the limitations to our understanding of whisker growth in phocid seals, we interpreted the isotopic data from whiskers under two alternate hypotheses of whisker replacement dynamics and the dietary periods that might be represented. Even under the most conservative hypothesis, it is clear from our data that changes in the marine food web of the west Spitsbergen coast have occurred over the last 20 years, and that these are detectable in the isotopes incorporated into higher trophic predators. Concluding which aspect of the food web has been modified is complicated by a lack of recent ringed seal dietary studies, a knowledge gap that should be prioritised as the climate continues to change.

Information on marine predator at‐sea distributions is key to understanding ecosystem and community dynamics and an important component of spatial management frameworks that aim to identify regions important for conservation. Tracking data from seabirds are widely used to define priority areas for conservation, but such data are often restricted to the breeding population. This also applies to penguins in Antarctica, where identification of important habitat for nonbreeders has received limited attention. Nonbreeding penguins are expected to have larger foraging distributions than breeding conspecifics, which may alter their interactions with physical environmental factors, conspecifics, other marine predators, and threats. We studied the movement behavior of nonbreeding Adélie penguins tracked during the 2016/2017 breeding season at King George Island in the South Shetland Islands, Antarctica. We quantify how nonbreeding penguins' horizontal moment behavior varies in relation to environmental conditions and assess the extent of spatial overlap in the foraging ranges of nonbreeders and breeders, which were tracked over several years. Nonbreeders increased their prey search and area‐restricted foraging behavior as sea surface temperature and bottom depths decreased, and in response to increasing sea ice concentration. Nonbreeders tended to transit (high directional movement) over the relatively deep Central Basin of the Bransfield Strait. The majority of foraging behavior occurred within the colder, Weddell Sea–sourced water of the Antarctic Coastal Current (incubation) and in the Weddell Sea (crèche). The utilization distributions of breeders and nonbreeders overlapped in the central Bransfield Strait. Spatial segregation was greater during the crèche stage of breeding compared to incubation and brood, because chick provisioning still constrained the foraging range of breeders to a scale of a few tens of kilometers, while nonbreeders commenced with premolt foraging trips into the Weddell Sea. Our results show that breeding and nonbreeding penguins may not be impacted similarly by local environmental variability, given that their spatial and temporal scales of foraging differ during some part of the austral summer. Our study highlights the need to account for different life history stages when characterizing foraging behavior of marine predator populations. This is particularly important for “sentinel” species monitored as part of marine conservation and ecosystem‐based management programs.