A bioenergetics model for estimating prey consumption by an Adélie penguin population in East Antarctica

Quantifying prey consumption by top predators is a crucial component of ecosystem-based management in the Southern Ocean. In this study, we developed a bioenergetics model to estimate prey consumption by a top predator, the Adélie penguin Pygoscelis adeliae. Our model predicts prey consumption throughout the breeding season and incorporates uncertainty in model parameters using Monte Carlo simulation. The model was parameterized with data obtained at Béchervaise Island, the site of a long-term monitoring program in East Antarctica. We parameterized the model (1) using 13 yr of penguin population data, (2) for a year in which penguins successfully reared their chicks (2001-2002) and (3) for a year with low breeding success (1998-1999). Daily per capita energy consumption during the breeding season averaged 4269 kJ d-1 (95% CI: 4187-4352 kJ d–1) and 4684 kJ d-1 (95% CI: 4596-4771 kJ d–1) for males and females, respectively. Over the entire breeding season a male breeder consumes 470 MJ (95% CI: 461-479 MJ) compared to 515 MJ (95% CI: 506-525 MJ) for a female. On average, the Béchervaise Island population of 1836 breeding pairs consumes 16447 MJ d-1 which amounts to 1809224 MJ during the breeding season. On the basis of variable breeding success and the proportion of krill and fish in their diet, we estimate that this population consumes 78 to 406 t of krill and 4 to 46 t of fish each breeding season. Our results demonstrate clear periods of peak consumption associated with the penguins’ breeding cycle

Density Can Be Misleading for Low-Density Species: Benefits of Passive Acoustic Monitoring

Climate-induced changes may be more substantial within the marine environment, where following ecological change is logistically difficult, and typically expensive. As marine animals tend to produce stereotyped, long-range signals, they are ideal for repeatable surveying. In this study we illustrate the potential for calling rates to be used as a tool for determining habitat quality by using an Antarctic pack-ice seal, the leopard seal, as a model. With an understanding of the vocal behavior of a species, their seasonal and diurnal patterns, sex and age-related differences, an underwater passive-acoustic survey conducted alongside a visual survey in an arc of 4,225 km across the Davis Sea, Eastern Antarctica, showed that while acoustic and visual surveys identified similar regions as having high densities, the acoustic surveys surprisingly identified the opposite regions as being 'critical' habitats. Density surveys of species that cannot be differentiated into population classes may be misleading because overall density can be a negative indicator of habitat quality. Under special circumstances acoustics can offer enormous advantage over traditional techniques and open up monitoring to regions that are remote, difficult and expensive to work within, no longer restricting long-term community assessment to resource-wealthy communities. As climatic change affects a broad range of organisms across geographic boundaries we propose that capitalizing on the significant advances in passive acoustic technology, alongside physical acoustics and population modeling, can help in addressing ecological questions more broadly

Estimating nest-level phenology and reproductive success of colonial seabirds using time-lapse cameras

1.Collecting spatially extensive data on phenology and reproductive success is important for seabird conservation and management, but can be logistically challenging in remote regions. Autonomous time‐lapse camera systems offer an opportunity to provide such coverage. 2.We describe a method to estimate nest‐level breeding phenology and reproductive success of colonial pygoscelid penguins using photographs from time‐lapse cameras. The method derives from stereotypical patterns of nest attendance, where predominantly two adults are present before and during laying, but switch to one adult during incubation. The switch approximates the date of clutch completion and is estimated by fitting a smoothing spline to daily nest attendance data, identifying candidate dates that switch from two adults to one and selecting the date when the first derivative of the spline is minimized. Clutch initiation and hatch dates are then estimated from the mean, species‐specific interval between laying (pygoscelid penguins typically lay two eggs) and the duration of the incubation period. We estimated these intervals for each species from historical field data. The phenology is adjusted when photographs indicate egg or chick presence prior to their estimated lay or hatch dates. The number of chicks alive in each study nest on its crèche date determines reproductive success estimates. The method was validated with concurrent direct observations for each species and then applied to a camera network in the Antarctic Peninsula region to demonstrate its utility. 3.Mean egg laying and incubation intervals from direct observations were similar within species across sites. In the validation study, the mean clutch initiation, hatch and crèche dates were generally equivalent between photographs and direct observations. Estimates of reproductive success were identical. Applying the method to a time‐lapse network suggested relatively high reproductive success for all species across the region and corroborated general understanding of latitudinal trends and species‐level plasticity in phenology. 4.The method accurately estimated phenology and reproductive success relative to direct observations and appears well‐suited to operationalize regional time‐lapse camera networks. The estimation method should be applicable for other seabirds with stereotypical nest attendance patterns from which breeding phenology could be estimated

Marine important bird and biodiversity areas for penguins in Antarctica: Targets for conservation action

Global targets for area-based conservation and management must move beyond threshold-based targets alone and must account for the quality of such areas. In the Southern Ocean around Antarctica, a region where key biodiversity faces unprecedented risks from climate change and where there is a growing demand to extract resources, a number of marine areas have been afforded enhanced conservation or management measures through two adopted marine protected areas (MPAs). However, evidence suggests that additional high quality areas could benefit from a proposed network of MPAs. Penguins offer a particular opportunity to identify high quality areas because these birds, as highly visible central-place foragers, are considered indicator species whose populations reflect the state of the surrounding marine environment. We compiled a comprehensive dataset of the location of penguin colonies and their associated abundance estimates in Antarctica. We then estimated the at-sea distribution of birds based on information derived from tracking data and through the application of a modified foraging radius approach with a density decay function to identify some of the most important marine areas for chick-rearing adult penguins throughout waters surrounding Antarctica following the Important Bird and Biodiversity Area (IBA) framework. Additionally, we assessed how marine IBAs overlapped with the currently adopted and proposed network of key management areas (primarily MPAs), and how the krill fishery likely overlapped with marine IBAs over the past five decades. We identified 63 marine IBAs throughout Antarctic waters and found that were the proposed MPAs to be adopted, the permanent conservation of high quality areas for penguin species would increase by between 49 and 100% depending on the species. Furthermore, our data show that, despite a generally contracting range of operation by the krill fishery in Antarctica over the past five decades, a consistently disproportionate amount of krill is being harvested within marine IBAs compared to the total area in which the fishery operates. Our results support the designation of the proposed MPA network and offer additional guidance as to where decision-makers should act before further perturbation occurs in the Antarctic marine ecosystem

Developing priority variables ("ecosystem Essential Ocean Variables" — eEOVs) for observing dynamics and change in Southern Ocean ecosystems

Reliable statements about variability and change in marine ecosystems and their underlying causes are needed to report on their status and to guide management. Here we use the Framework on Ocean Observing (FOO) to begin developing ecosystem Essential Ocean Variables (eEOVs) for the Southern Ocean Observing System (SOOS). An eEOV is a defined biological or ecological quantity, which is derived from field observations, and which contributes significantly to assessments of Southern Ocean ecosystems. Here, assessments are concerned with estimating status and trends in ecosystem properties, attribution of trends to causes, and predicting future trajectories. eEOVs should be feasible to collect at appropriate spatial and temporal scales and are useful to the extent that they contribute to direct estimation of trends and/or attribution, and/or development of ecological (statistical or simulation) models to support assessments. In this paper we outline the rationale, including establishing a set of criteria, for selecting eEOVs for the SOOS and develop a list of candidate eEOVs for further evaluation. Other than habitat variables, nine types of eEOVs for Southern Ocean taxa are identified within three classes: state (magnitude, genetic/species, size spectrum), predator–prey (diet, foraging range), and autecology (phenology, reproductive rate, individual growth rate, detritus). Most candidates for the suite of Southern Ocean taxa relate to state or diet. Candidate autecological eEOVs have not been developed other than for marine mammals and birds. We consider some of the spatial and temporal issues that will influence the adoption and use of eEOVs in an observing system in the Southern Ocean, noting that existing operations and platforms potentially provide coverage of the four main sectors of the region — the East and West Pacific, Atlantic and Indian. Lastly, we discuss the importance of simulation modelling in helping with the design of the observing system in the long term. Regional boundary: south of 30°S

The retrospective analysis of Antarctic tracking data project

The Retrospective Analysis of Antarctic Tracking Data (RAATD) is a Scientific Committee for Antarctic Research project led jointly by the Expert Groups on Birds and Marine Mammals and Antarctic Biodiversity Informatics, and endorsed by the Commission for the Conservation of Antarctic Marine Living Resources. RAATD consolidated tracking data for multiple species of Antarctic meso- and top-predators to identify Areas of Ecological Significance. These datasets and accompanying syntheses provide a greater understanding of fundamental ecosystem processes in the Southern Ocean, support modelling of predator distributions under future climate scenarios and create inputs that can be incorporated into decision making processes by management authorities. In this data paper, we present the compiled tracking data from research groups that have worked in the Antarctic since the 1990s. The data are publicly available through biodiversity.aq and the Ocean Biogeographic Information System. The archive includes tracking data from over 70 contributors across 12 national Antarctic programs, and includes data from 17 predator species, 4060 individual animals, and over 2.9 million observed locations

The retrospective analysis of Antarctic tracking data project

The Retrospective Analysis of Antarctic Tracking Data (RAATD) is a Scientific Committee for Antarctic Research project led jointly by the Expert Groups on Birds and Marine Mammals and Antarctic Biodiversity Informatics, and endorsed by the Commission for the Conservation of Antarctic Marine Living Resources. RAATD consolidated tracking data for multiple species of Antarctic meso- and top-predators to identify Areas of Ecological Significance. These datasets and accompanying syntheses provide a greater understanding of fundamental ecosystem processes in the Southern Ocean, support modelling of predator distributions under future climate scenarios and create inputs that can be incorporated into decision making processes by management authorities. In this data paper, we present the compiled tracking data from research groups that have worked in the Antarctic since the 1990s. The data are publicly available through biodiversity.aq and the Ocean Biogeographic Information System. The archive includes tracking data from over 70 contributors across 12 national Antarctic programs, and includes data from 17 predator species, 4060 individual animals, and over 2.9 million observed locations.Supplementary Figure S1: Filtered location data (black) and tag deployment locations (red) for each species. Maps are Lambert Azimuthal projections extending from 90° S to 20° S.Supplementary Table S1: Names and coordinates of the major study sites in the Southern Ocean and on the Antarctic Continent where tracking devices were deployed on the selected species (indicated by their 4-letter codes in the last column).Online Table 1: Description of fields (column names) in the metadata and data files.Supranational committees and organisations including the Scientific Committee on Antarctic Research Life Science Group and BirdLife International. National institutions and foundations, including but not limited to Argentina (Dirección Nacional del Antártico), Australia (Australian Antarctic program; Australian Research Council; Sea World Research and Rescue Foundation Inc., IMOS is a national collaborative research infrastructure, supported by the Australian Government and operated by a consortium of institutions as an unincorporated joint venture, with the University of Tasmania as Lead Agent), Belgium (Belgian Science Policy Office, EU Lifewatch ERIC), Brazil (Brazilian Antarctic Programme; Brazilian National Research Council (CNPq/MCTI) and CAPES), France (Agence Nationale de la Recherche; Centre National d’Etudes Spatiales; Centre National de la Recherche Scientifique; the French Foundation for Research on Biodiversity (FRB; www.fondationbiodiversite.fr) in the context of the CESAB project “RAATD”; Fondation Total; Institut Paul-Emile Victor; Programme Zone Atelier de Recherches sur l’Environnement Antarctique et Subantarctique; Terres Australes et Antarctiques Françaises), Germany (Deutsche Forschungsgemeinschaft, Hanse-Wissenschaftskolleg - Institute for Advanced Study), Italy (Italian National Antarctic Research Program; Ministry for Education University and Research), Japan (Japanese Antarctic Research Expedition; JSPS Kakenhi grant), Monaco (Fondation Prince Albert II de Monaco), New Zealand (Ministry for Primary Industries - BRAG; Pew Charitable Trusts), Norway (Norwegian Antarctic Research Expeditions; Norwegian Research Council), Portugal (Foundation for Science and Technology), South Africa (Department of Environmental Affairs; National Research Foundation; South African National Antarctic Programme), UK (Darwin Plus; Ecosystems Programme at the British Antarctic Survey; Natural Environment Research Council; WWF), and USA (U.S. AMLR Program of NOAA Fisheries; US Office of Polar Programs).http://www.nature.com/sdataam2021Mammal Research Institut